Publications by Dr Anna Jordanous

Artificial intelligence has a rich history in literature; fiction has shaped how we view artificial agents and their capacities in the real world. This paper looks at embodied examples of human-machine co-creation from the literature of the Long 18th Century (1650–1850), examining how older depictions of creative machines could inform and inspire modern day research. The works are analyzed from the perspective of design fiction with special focus on the embodiment of the systems and the creativity exhibited by them. We find that the chosen examples highlight the importance of recognizing the environment as a major factor in human-machine co-creative processes and that some of the works seem to precede current examples of artificial systems reaching into our everyday lives. The examples present embodied interaction in a positive, creativity-oriented way, but also highlight ethical risks of human-machine co-creativity. Modern day perceptions of artificial systems and creativity can be limited to some extent by the technologies available; fictitious examples from centuries past allow us to examine such limitations using a Design Fiction approach. We conclude by deriving four guidelines for future research from our fictional examples: 1) explore unlikely embodiments; 2) think of situations, not systems; 3) be aware of the disjunction between action and appearance; and 4) consider the system as a situated moral agent.

This paper reflects on a seminal work in the history of AI and representation: Rodney Brooks' 1991 paper Intelligence without Representation. Brooks advocated the removal of explicit representations and engineered environments from the domain of his robotic intelligence experimentation, in favour of an evolutionary-inspired approach using layers of reactive behaviour that operated independently of each other. Brooks criticised the current progress in AI research and believed that removing complex representation from AI would help address problematic areas in modelling the mind. His belief was that we should develop artificial intelligence by being guided by evolutionary development of our own intelligence, and that his approach mirrored how our own intelligence functions. Thus the field of behaviour-based robotics emerged. This paper offers a historical analysis of Brooks' behaviour-based robotics approach and its impact in artificial intelligence and cognitive theory at the time, as well as in modern-day approaches to AI.

A significant test for software is when it is tasked with replicating human performance, as was the case recently with creative software and the commercial project Beyond the Fence (undertaken for a television documentary Computer Says Show). The remit of the Beyond the Fence project was to use computer software as much as possible to produce a musical show billed as `the world's first computer-generated musical'. Several computational creativity systems were used in the production of this musical, which was performed in London's West End for a two week run in 2016. This paper considers the challenge of evaluating this project. Current computational creativity evaluation methods are ill-suited to evaluating projects involving creative input from multiple systems and people. Following recent inspiration within computational creativity research from interaction design, here the DECIDE evaluation framework is used to evaluate the Beyond the Fence project along two questions: (1) To what extent is the project successful? and (2) To what extent does this project demonstrate computational creativity? Evaluation lets us conclude that this was a reasonably successful achievement of the task of using computational generation in producing a credible musical show. Lessons have been learned for future computational creativity projects though, particularly for affording creative software more agency and enabling software to interact with other creative partners. Upon reflection, the DECIDE framework emerges as a useful evaluation `checklist' (if not a tangible operational methodology) for the evaluation of multiple creative systems participating in a single creative task.

The production of digital critical editions of texts using TEI is now a widely-adopted procedure within digital humanities. The work described in this paper extends this approach to the publication of gnomologia (anthologies of wise sayings) , which formed a widespread literary genre in many cultures of the medieval Mediterranean. These texts are challenging because they were rarely copied straightforwardly ; rather , sayings were selected , reorganised , modified or re-attributed between manuscripts , resulting in a highly interconnected corpus for which a standard approach to digital publication is insufficient. Focusing on Greek and Arabic collections , we address this challenge using semantic web techniques to create an ecosystem of texts , relationships and annotations , and consider a new model – organic , collaborative , interconnected , and open-ended – of what constitutes an edition. This semantic web-based approach allows scholars to add their own materials and annotations to the network of information and to explore the conceptual networks that arise from these interconnected sayings

On the 15th June 2017, a diverse group of researchers in computing, arts, sciences, and other fields of cultural endeavour met at the Waldegrave Drawing Room, St Mary's University, to discuss serendipity – "the art of making an unsought finding" [11]. The core goals of the symposium were to relate various understandings of serendipity from different disciplines, and to discuss contentious questions such as whether/how serendipity can be supported or simulated by computational means.

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

Computational creativity is the modelling, simulating or replicating of creativity computationally. In examining and learning from these `creative systems', from what perspective should the creativity of a system be considered? Are we interested in the creativity of the system's output? Or of its creative processes? Features of the system? Or how it operates within its environment? Traditionally computational creativity has focused more on creative systems' products or processes, though this focus has widened recently. Creativity research offers the Four Ps of creativity: Person/Producer, Product, Process and Press/Environment. This paper presents the Four Ps, explaining each in the context of creativity research and how it relates to computational creativity. To illustrate the usefulness of the Four Ps in taking broader perspectives on creativity in its computational treatment, the concepts of novelty and value are explored using the Four Ps, highlighting aspects of novelty and value that may otherwise be overlooked. Analysis of recent research in computational creativity finds that although each of the Four Ps appears in the body of computational creativity work, individual pieces of work often do not acknowledge all Four Ps, missing opportunities to widen their work's relevance. We can see, though, that high-status computational creativity papers do typically address all Four Ps. This paper argues that the broader views of creativity afforded by the Four Ps is vital in guiding us towards more comprehensively useful computational investigations of creativity. This paper is available for free download during September 2016 at http://tandfonline.com/doi/full/10.1080/09540091.2016.1151860

While recent debate has often focused on a reified 'cultural value' (whether opposed to or aligned with monetary value), this article treats 'value' as a verb and investigates the acts of valuing in which people engage. Through ethnographic research in London's electronic music scene and social network analysis of the SoundCloud audio sharing website (which is dominated by electronic dance music and, to a lesser extent, hip hop), it uncovers substantial patterns of geographical inequality. London is found at the very centre of a network of valuing relationships, in which New York and Los Angeles occupy the next most privileged locations, followed by Berlin, Paris, and Chicago. Cities outside Western Europe and the Anglophone world tend to occupy peripheral positions in the network. This finding suggests that location plays a major role in the circulation of value, even when we might expect that role to have been curtailed by an ostensibly 'placeless' medium for the distribution and valuing of music. While there are reasons for the metropolitan emplacedness of dance music – given the importance of the relationship between production, consumption, and live DJing – the privileging of particular cities also mirrors patterns of inequality in the wider cultural economy. That London should appear so supremely privileged reflects both the exporting strength of British creative industries and the imbalanced nature of the UK's cultural economy.

Computational creativity is a flourishing research area, with a variety of creative systems being produced and developed. Creativity evaluation has not kept pace with system development with an evident lack of systematic evaluation of the creativity of these systems in the literature. This is partially due to difficulties in defining what it means for a computer to be creative; indeed, there is no consensus on this for human creativity, let alone its computational equivalent. This paper proposes a Standardised Procedure for Evaluating Creative Systems (SPECS). SPECS is a three-step process: stating what it means for a particular computational system to be creative, deriving and performing tests based on these statements. To assist this process, the paper offers a collection of key components of creativity, identified empirically from discussions of human and computational creativity. Using this approach, the SPECS methodology is demonstrated through a comparative case study evaluating computational creativity systems that improvise music.

Background in musical improvisation and creativity. What makes musical improvisation creative? And what exactly is it that justifies one improviser being described as more creative than another? For a clearer understanding, it is a practical necessity to use an approach such as those of Berliner (1994) and Gibbs (2010), who make the study of improvisational creativity more tangible by identifying key constituent parts, rather than treat creativity as ineffable (Bailey 1993). Background in computational linguistics. The log likelihood ratio statistic can be used to compare two sets of texts (corpora) to examine word distribution patterns (Rayson & Garside 2000, Dunning 1993). Using this statistic, words are identified which are associated with academic papers on creativity. Lin's similarity measure (Lin 1998) is then used as a basis for clustering words with similar meanings using the algorithm Chinese Whispers (Biemann 2006). Analysis of the clusters reveals fourteen key components of creativity. Aims. To model creativity in musical improvisation by identifying components of creativity using computational linguistics techniques and understanding how each contributes to creativity in improvisation. Main contribution. The paper presents an empirical, language-based approach to understanding creativity in musical improvisation. This approach is based upon treating creativity as having common features that transcend different types of creativity but that vary in importance depending on the type of creativity. Fourteen key components of creativity are identified from an analysis of a corpus of texts on creativity. A study is then conducted to investigate the relative importance of each of these components in musical improvisational. All fourteen components are considered relevant to some degree, but particular significance is attached to three of them: the ability to communicate and interact, the possession of relevant musical knowledge and skills, and emotional engagement and intention. It is notable that the products of improvisation are relatively less important than these process-based aspects. Implications. The work provides a model of musical improvisational creativity as a set of guidelines or benchmarks for evaluating how creative a musical improviser is. Such a detailed understanding helps improvisers identify what areas to work on in order to develop their creativity (Gibbs 2010).

When suitable accompanists are not available to a soloist musician, an alternative possibility is to use computer-generated accompaniment. A computer accompanist should interact with the soloist and adapt to the soloist's playing as a human accompanist would, both reacting to expressive nuances of tempo and to unintentional errors such as wrong or mistimed notes. Over the past 25 years, accompaniment systems have been developed, all of which employ some form of score following: the process of following a musician's progress through the score of a piece during performance. This work considers the role of score following in automatic accompaniment. In this investigation we developed a computer accompanist that employs score following. Our computer musician uses Hidden Markov Models to model the score by metrical structure and to provide accompaniment to a soloist playing monophonic music in real time, as the soloist is playing. Working with MIDI input/output, it tracks tempo fluctuations, anticipates the soloist's next note and supports some amount of unintentional deviation from the score. Qualitative evaluation, by human testers, and quantitative evaluation, using measurable criteria taken from MIREX, reported that the system performs adequately. We then used interviews with eight human accompanists to consider how well a score following system models the accompaniment process. This evaluation raises questions about the musical interaction between soloist and accompanist that have received relatively little attention. The information we gathered from interviews suggests the importance of other aspects of accompaniment, such as the sharing of shape of the performance between musicians, rather than treating the accompanist as purely subservient. We discuss the implications of these issues for the design of automated accompanists.

Computational creativity research has produced many computational systems that are described as 'creative'. Historically, these 'creative systems' have not received much in terms of evaluation of the actual creativity of the systems, although this has recently attracted more attention as a research perspective. As a scientific research community, computational creativity researchers can benefit from more systematic/standardised approaches to evaluation of the creativity of our systems, to help us progress in understanding creativity and modelling it computationally. A methodology for creativity evaluation should accommodate different manifestations of creativity but also requires a clear, definitive statement of the tests used for evaluation. Here a historical perspective is given on how computational creativity researchers have evaluated (or not evaluated) the creativity of their systems, considering contextual reasons behind this. Different evaluation approaches and frameworks are currently available, though it is not yet clear which (if any) of several recently proposed methods are emerging as the preferred options to use. The Standardised Procedure for Evaluating Creative Systems (SPECS) forms an overarching set of guidelines for how to tackle evaluation of creative systems and can incorporate recent proposals for creativity evaluation. To help decide which evaluation method is best to use, this chapter concludes by exploring five meta-evaluation criteria devised from cross-disciplinary research into good evaluative practice. Together, these considerations help us explore best practice in computational creativity evaluation, helping us develop the tools we have available to us as computational creativity researchers.

This study addresses the challenge of adapting current beat tracking algorithms, predominantly trained on Western music, to the rhythmic complexities of Salsa, a genre rich in syncopations and polyrhythms. Using training meth- ods that minimise the need for extensive annotated data, we benchmark the adaptability of two established models: BeatNet and BöckTCN, on our newly introduced beat and downbeat annotated Salsa dataset. We find that, on Salsa music, models trained with Salsa largely outperform mod- els trained without any Salsa, nearly matching the accuracy of these models on Western music. This research not only establishes a baseline for beat and downbeat tracking per- formance in Salsa music but also contributes to the broader goal of developing more adept music information retrieval systems. We also contribute a 40-song Salsa dataset for beat and downbeat tracking research in this genre.

This study explores the facilitation of ideation in the creative process through the interaction with AI-imagery tools. We developed a range of co-creative methodologies for ideation and evaluated them in an experimental study with creative experts. The creativity of the sys tem was assessed using the SPECS method, while attitudes towards future adoption were evaluated using the UTAUT scale. Inspiration and self-reflection were also measured to assess the ideation impact to the participants. Results indicate a strong inclination among participants in adopting AI-imagery tools for ideation. Correlation between SPECS and UTAUT suggests the potential for predicting system acceptance and future adoption through creativity measurement scales. Interviews with participants underscored design considerations, such as maintaining balance between surprise and control and preserving the tool's artistic interpretation. This study highlights the positive reception of AI-imagery tools for ideation and underscores the potential of combining SPECS and UTAUT as an evaluation methodology for co-creative systems.

This study addresses the challenge of adapting current beat tracking algorithms, predominantly trained on Western music, to the rhythmic complexities of Salsa, a genre rich in syncopations and polyrhythms. We benchmark the adaptability of three established models: BeatNet, Wavebeat, and Böck TCN, using our own newly introduced beat-annotated Salsa dataset and focusing on training methods that minimize the need for extensive annotated data. We find that, on Salsa music, models trained with popular datasets and fine-tuned with Salsa generally outperform models trained under other training conditions. This research not only establishes a baseline for beat tracking performance in Salsa music but also contributes to the broader goal of developing more universally adept music information retrieval systems.

Incredible as they may be, Large Language Models (LLMs) have their limitations. While they generate high-quality texts, excel at stylistic reproduction, and tap into an immense pool of information, they can produce wildly inaccurate responses. The hype around LLMs led to them being characterized as "reasoning", "sentient", or "knowing" like humans. We examine these characterizations and discuss what LLMs can't do and what they are surprisingly good at. LLMs are still susceptible to traditional issues with AI, probabilities are not knowledge, and they are not in the world. Nonetheless, LLMs, despite not being human, have great potential to perform various creative tasks. We conclude that LLMs are beyond "mere generation" and perceivable as creative, but we may need to reassess some frameworks for creativity evaluation.

This paper examines issues of diversity and representa- tion in the International Conference on Computational Creativity (ICCC), evaluating the diversity of authors, content and existing creative systems. We consider: the diversity of cultural context of published systems; di- versity of authors in terms of gender and culture; how the pandemic affected diversity; and trends in content of accepted papers. The study covers a period of six con- secutive years around the COVID-19 pandemic (2017- 22), to better understand the impact of the pandemic on diversity. The research team includes individuals from different career stages and research interests, who bring diverse perspectives to the analysis. We evidence the need for greater diversity in both authorship and con- tent, as well as in the creative systems discussed in the proceedings. The paper concludes with recommenda- tions for increasing diversity and representation in the field of computational creativity.

Research in computational co-creativity frequently focuses on technical performance of computational systems and subjective quality of end-products. How computational co-creative systems impact the creative process of users has received less attention. This paper reports on a two-way double-blind crossover study to investigate how the creative processes of thirteen electronic music producers were impacted while interacting with two computational co-creative systems providing melody suggestions. The two systems shared a common user interface, however, the 'smart' co-creative system suggested melodies that expanded on producers' input melodies, while the 'naive' co-creative system produced melodies unrelated to the producers' inputs. To capture participants' subjective experience, aspects of creativity were rated on Likert scales and further explored with semi-structured interviews. Each system's output and producer's intermediate melodies were compared for change (in compositions), dissimilarity (new AI generated elements), and adoption (into melodies). Producers considered the 'smart' co-creative system to produce the most novel and valuable contributions to their process. Outputs from the 'naive' co-creative system were judged to be more dissimilar than smart expansions. Nonetheless, the changes that producers incorporated into their intermediate melodies were similar between the systems. This study suggests that co-creative interactions can stimulate the creative process by offering both related and unrelated musical suggestions.

In recent years, emojis have become a key part of computer-mediated communication (CMC). This stems from the fact that they act as nonverbal cues which are difficult to convey when communicating using simple text. Just as a picture is worth a thousand words, the same can be said for an emoji. In this paper, we present a creative system, Emojinator, that generates emojis us- ing visual blending to represent a diverse range of emo- tions. Unlike previous emoji generation work, fuzzy logic was incorporated to enable Emojinator to make decisions. A user study was conducted to evaluate the output, along with the creative tripod method to as- sess Emojinator's creativity. The results from the sur- vey show that for more than half the emojis, at least 50 percent of participants agreed or strongly agreed that the emoji represented the stated emotion. Evaluation through the creative tripod method showed that the sys- tem is skillful and imaginative but could be more appre- ciative. Therefore, further refinement may be needed to make the system more creative. However, the success of this novel approach to emoji creation opens up new directions for future work.

With many options for text preprocessing techniques, choosing the most efficient methodology is important for both accuracy and computational expense. Online text often contains non-standard English, spelling errors, colloquialisms, emojis, slang and many other variations that affect current natural language processing tools, with no clear guidelines for preprocessing this type of text. In this work we analyse text preprocessing techniques using a data set of online reviews scraped from iTunes and Google Play store. The objective is to measure the efficacy of different combinations of these techniques to maximise the amount of detected sentiment in a dataset of 438,157 reviews. Sentiment detection was performed by two state-of-the-art sentiment analysers (RoBERTa and VADER). Statistical analysis of the results suggest preprocessing strategies for maximising sentiment detected within mental health app reviews and similar text formats.

In this pilot study, we explore the Variational Autoencoder as a computational model for conceptual spaces in a social interaction context. Conceptually, the Variational Autoencoder is a natural fit for this purpose. We apply this idea in an agent-based social creativity simulation to explore and understand the effects of social interactions on adapting conceptual spaces. We demonstrate a simple simulation setup and run experiments with a focus on establishing a baseline. While ongoing work needs to identify if adaption was appropriate, the results so far suggest that the Variational Autoencoder appears to adapt to new artefacts and has potential for modelling conceptual spaces.

Poetry generation within style constraints has many creative challenges, despite the recent advances in Transformer models for text generation. We study 1) how overfitting of various versions of GPT-2 models affects the quality of the generated text, and 2) which model is better at generating text in a specific style. For that purpose, we propose a novel setup for text evaluation with neural networks. Our GPT-2 models are trained on datasets of collected works of the two Romantic-era poets: Byron and Shelley. With some models, overfitting manifests by producing malformed samples, with others, the samples are always well-formed, but contain increasingly higher levels of n-grams duplicated from the original corpus. This behaviour can lead to incorrect evaluations of generated text because the plagiarised output can deceive neural network classifiers and even human judges. To determine which model is better at preserving style before it becomes overfitted, we conduct two series of experiments with BERT-based classifiers. Overall, our results provide a novel way of selecting the right models for fine-tuning on a specific dataset, while highlighting the pitfalls that come with overfitting, like reordering and replicating text, towards more credible creative text generation.

Is style reproduction a valid computational creativity task? Does producing output 'in the style of' an existing creator contribute to computational creativity research? Where is the creativity in imitation or replication of an existing style, and where does style reproduction fall into what has been criticised as `pastiche' rather than credible creative activity? This paper tackles these debates, which have been under-addressed in computational creativity literature. We review the presentation of past work in style reproduction, and consider the fit of such work into evolving definitions of computational creativity research. As part of this, we consider style reproduction itself as a creative task, both within and outside computational forms. We discuss various points of interest that emerge in the analysis, such as control in the creative process, intentionality and effort. Our work gives a more objective understanding of the level of creativity present in style generation, and specifically what value it brings to computational creativity research.

Should we pursue a state-of-the-art in Computational Creativity? The activity of 'SOTA-chasing', or working towards beating performance standards achieved by the current state of the art, is typical in many research disciplines relevant to computational creativity such as Machine Learning or Natural Language Generation (SOTA). Computational Creativity (CC) research does not typically engage with SOTA-type benchmarks. Consequently, it becomes harder to objectively identify high-performing systems in a creative domain (area of creative application), despite our research efforts building significant bodies of work in several domains. This paper critically engages with the use of SOTA in other related disciplines and explores the idea of working with SOTA-based evaluation in CC. The paper offers recommendations for (careful) use of SOTA to invigorate and direct CC progress.

The 7th AISB Symposium on Computational Creativity (CC@AISB2020/21) took place online during April 2021. As event organisers, we report on the event, its ongoing history at the AISB and its future.

In this paper, we present a fresh perspective at co- creativity - using human development as a blueprint, we argue that fostering human creativity is a natural evolu- tion of creative machines. We introduce the notion of a "humble" creative machine - one that is less concerned with demonstrating its own independence, and instead uses its (potentially advanced) creative abilities to cul- tivate human creativity. We present characteristics of Humble Creative Machines and offer examples of ex- isting (almost) humble machines.

The purpose of this ongoing research is to better un- derstand the potential contributions that computers can play in sit- uations where people interact with computers towards creative pur- suits and goals. Past research has provided sets of definitions of dif- ferent roles that a computer plays in human-computer creative col- laboration. Thus far, we look into the advantages and limitations of having such roles. In particular, this paper contributes an analysis and categorisation of the coverage of existing role classifications for computational participants in co-creativity. This analysis is comple- mented by a comparative review of the use of roles to understand and structure creative collaboration between people only (i.e. without any computational participants involved). Our wider project investigates whether these defined sets of roles are a. adequate and b. helpful for understanding the perception of computational contributions in co-creativity, with a study planned to investigate the roles of current systems in practice. This project considers both co-creative computer systems that currently exist, and systems that could potentially exist in the future. Our goal is to reach a point where the perception of what is possible in human-computer co-creative collaboration is en- abled and boosted (but not constrained) by a definitive set of roles.

People's emotions are not always detectable, e.g. if a person has difficulties/lack of skills in expressing emotions, or if people are geographically separated/communicating online). Brain-computer interfaces (BCI) could enhance non-verbal communication of emotion, particularly in detecting and responding to users' emotions e.g. music therapy, interactive software. Our pilot study Music Emotion Capture 1 detects, models and sonifies people's emotions based on their real-time emotional state, measured by mapping EEG feedback onto a valence-arousal emotional model 2 based on [3]. Though many practical applications emerge, the work raises several ethical questions, which need careful consideration. This poster discusses these ethical issues. Are the work's benefits (e.g. improved user experiences; music therapy; increased emotion communication abilities; enjoyable applications) important enough to justify navigating the ethical issues that arise? (e.g. privacy issues; control of representation of/reaction to users' emotional state; consequences of detection errors; the loop of using emotion to generate music and music affecting the emotion, with the human in the process as an "intruder"). 1 Langroudi, G., Jordanous, A., & Li, L. (2018). Music Emotion Capture: emotion-based generation of music using EEG. Emotion Modelling and Detection in Social Media and Online Interaction symposium @ AISB 2018, Liverpool. 2 Paltoglou, G., & Thelwall, M. (2012). Seeing stars of valence and arousal in blog posts. IEEE Transactions on Affective Computing, 4(1) [3] Russell, J.A. (1980). 'A circumplex model of affect', Journal of Personality and Social Psychology, 39

While computational aesthetic evaluation has been applied to images and visual output, it is not as widely employed for generative music systems. Computational aesthetic evaluation is not to be confounded with numerical evaluation of the system's output; such a notion is in danger of offering a reduced and impoverished interpretation of the aesthetic experience, which is innately dialogical, between the creator or the user, the sociological context, and the creative process or product. This paper reviews common computational aesthetic measures that have been used for musical applications, whilst arguing for a pragmatist perspective and a framework foregrounding the primacy of intentionality and agency in inducing aesthetic responses.

People's emotions are not always obviously detectable, due to difficulties expressing emotions, or geographic distance (e.g. if people are communicating online). There are also many occasions where it would be useful for a computer to be able to detect users' emotions and respond to them appropriately. A person's brain activity gives vital clues as to emotions they are experiencing at any one time. The aim of this project is to detect, model and sonify people's emotions. To achieve this, there are two tasks: (1) to detect emotions based on current brain activity as measured by an EEG device; (2) to play appropriate music in real-time, representing the current emotional state of the user. Here we report a pilot study implementing the Music Emotion Capture system. In future work we plan to improve how this project performs emotion detection through EEG, and to generate new music based on emotion-based characteristics of music. Potential applications arise in collaborative/assistive software and brain-computer interfaces for non-verbal communication.

This work investigates the impact of constraints on the perceived creativity of the output of narrative generating systems, in order to understand what level of constraint application results in the most creative output. To achieve this, software is written that generates short stories, using adjustable levels of constraint meant to reflect those utilised by other narrative generating systems. These systems are presented at different positions along a spectrum, which we posit arises from the application of constraint. The creativity of the output is then assessed by human evaluators. The results are promising and show a clear variation of response based on the level of constraint imposed on the narrative generation process. The results show a sweet spot for maximal creativity closer to the less constrained end of the spectrum, which demonstrates the potential for more creative software by the relaxing of constraints.

The evaluation of computational creativity systems is increasingly becoming part of standard practice in computational creativity research, particularly with recent development in evaluation tools. One matter that can cause confusion, however, is in distinguishing between the concepts of creativity and quality/value. These two concepts are highly interrelated, to the point that it is difficult (and perhaps inappropriate) to define creativity without incorporat- ing quality judgements into that definition. Several examples exist, however, where creativity evaluation has been confused with quality judgments, leading to less grounded evaluative results. Many computational creativity projects aim to produce high quality results; this is a worthy research aim. If, however, the aim of a computational creativity research project is to make as creative a system as possible, then a more careful approach is needed that acknowledges and understands the differences - and also the overlaps - between creativity and quality. This paper critically investigates the concepts of creativity and quality (and how they are related). It offers warning examples showing the dangers of conflating the two concepts. These are followed by practical examples of how to incorporate value judgements into the evaluation of creativity of software, to further our overall pursuit of building more creative computational systems.

How are computers typically perceived in co-creativity scenarios? And how does this affect how we evaluate computational creativity research systems that use cocreativity? Recent research within computational creativity considers how to attribute creativity to computational agents within co-creative scenarios. Human evaluation forms a key part of such attribution or evaluation of creative contribution. The use of human opinion to evaluate computational creativity, however, runs the risk of being distorted by conscious or subconscious bias. The case study in this paper shows people are significantly less confident at evaluating the creativity of a whole co-creative system involving computational and human participants, compared to the (already tricky) task of evaluating individual creative agents in isolation. To progress co-creativity research, we should combine the use of co-creative computational models with the findings of computational creativity evaluation research into what contributes to software creativity.

The increasing popularity of computational creativity (CC) in recent years gives rise to the need for educational resources. This paper presents several modules that together act as a guide for developing new CC courses as well as improving existing curricula. As well as introducing core CC concepts, we address pedagogical approaches to this interdisciplinary subject. An accessible overview of the field lets this paper double as an introductory tutorial to computational creativity.

Predictability is the polar opposite of originality, and as such it is a notable obstacle that should be overcome in the pursuit of computational creativity. Accurately modelling a human's understanding of predictability would be a monumental task, requiring a contextually rich network of social interaction, literature, news, and media. However, by artificially instilling a computer with some basic ideas about what is predictable in a given scenario, it can begin to gain an understanding of how to subvert expectation. This project attempts to implement such a process into a specially designed story generation system known as Chronicle, inspired by Vladímir Propp's Morphology of the Folk Tale. Chronicle aims to fine-tune narrative direction and progression in a system modelled on predictability. Decisions made during the story generation process are based on probabilities defined by the expectations of the typical reader, and are amassed to formulate an overall predictability rating. The decision making process is manipulated by the system in order to pursue a customisable predictability target. Chronicle was demonstrably accurate at evaluating its output in some cases, and less accurate in other cases. Further refinement is required to increase its efficacy, but it presents a promising step towards negotiating predictability in computational creativity.

Beyond the Fence is a commercial project, undertaken for a television documentary, that has produced a musical show billed as "the world's first computer-generated musical". Several computational creativity systems have been used in the production of various parts of this musical, which has been performed in London's West End for a two week run in 2016. Having been involved in this project as an informed commentator who was not involved in creating any of the software, I consider two questions that together form the main contribution of this paper: (1) To what extent is the project successful? and (2) To what extent does this project demonstrate computational creativity? Investigations into these questions show that Beyond the Fence has successfully shown how existing creative software can indeed be used to create a plausible and acceptable musical. The resulting musical has been moderately well-received by most critics, though standards are raised high for computational creativity in the public eye. The project has also raised the profile of computational creativity research. Some some useful lessons have also been highlighted for computational creativity; in particular, computational creativity should include more than merely replicating norms, and completing independent tasks within the creative process (with little feedback or collaboration between tasks). The impact for computational creativity is that for these larger scale multi-system public-facing projects to be more successful, we are reminded of the need to develop as well as replicate human creative achievements, and to allow our systems to be able to communicate and refine work as well as offer inspirational material.

'Non-player characters (NPCs)' can present well-crafted behaviours and evoke engaging and immersive player experiences but such behaviour in current NPCs is illusory and only achievable within a controlled and linear/fixed video game context. NPCs struggle greatly to portray flexible or creative behaviours within an adaptive or procedurally generated environment and this is even more apparent in their relationship with sound. This paper posits that recent theoretical developments in cognitive psychology offer significant opportunity to advance NPC-AI and proposes that an intelligence framework, based upon Sonic Virtuality and integrated within an NPC, would offer distinct advantages over current systems. To illustrate this vision, a roadmap for future work is laid out using Sonic Virtuality as the foundation for a 'synthetic listener'; an NPC capable of responding to procedurally generated and external (player-domain) audio. As a philosophical exploration, underlying principles are considered for other perception modalities, presenting an avenue of games-AI research that, ultimately, could dramatically improve NPC- 'humanness' and evoke a player-immersion and presence equivalent to linear/fixed AI but in much bigger, more complex virtual worlds.

During research to develop the Standardised Procedure for Evaluating Creative Systems (SPECS) methodology for evaluat- ing the creativity of 'creative' systems, in 2011 an evaluation case study was carried out. The case study investigated how we can make a 'snapshot' decision, in a short space of time, on the creativity of systems in various domains. The systems to be evaluated were presented at the International Computational Creativity Conference in 2011. Evaluation was performed by people whose domain expertise ranges from expert to novice, depending on the system. The SPECS methodology was used for evaluation, and was compared to two other creativity evaluation methods (Ritchie's criteria and Colton's Creative Tripod) and to results from surveying people's opinion on the creativity of the systems under investigation. Here, we revisit those results, considering them in the context of what these systems have contributed to computational creativity development. Five years on, we now have data on how influential these systems were within computational creativity, and to what extent the work in these systems has influenced further developments in computational creativity research. This paper investigates whether the evaluations of creativity of these systems have been helpful in predicting which systems will be more influential in computational creativity (as measured by paper citations and further development within later computational systems). While a direct correlation between evaluative results and longer term impact is not discovered (and perhaps too simplistic an aim, given the factors at play in determining research impact), some interesting alignments are noted between the 2011 results and the impact of papers five years on.

Data are everywhere. Often the sheer quantities of data that we store or archive in repositories or digital libraries make it difficult to navigate data; information in the data is obscured, particularly where we have Big Data. Traditionally, we record metadata on our data items to assist data classification and some information retrieval. The Semantic Web enables us to further unlock and enrich our data, by exploring how different data are related or connected. Using ontologies and Linked Data we can declare, navigate and discover semantic relationships. Relationships exist both locally, within the data, and globally, such that we can enhance our data with information retrieved from a wider context. To illustrate how the application of Semantic Web technologies aids data discovery and information retrieval, I discuss two case studies: (1) Sharing Ancient Wisdoms (SAWS), a Dynamic Library of information on selected ancient wisdom literature; and (2) the DEFRA DTC archive, a repository of data about freshwater quality in the UK.

From what perspective should creativity of a system be considered? Are we interested in the creativity of the system's out- put? The creativity of the system itself? Or of its creative processes? Creativity as measured by internal features or by external feedback? Traditionally within computational creativity the focus had been on the creativity of the system's Products or of its Processes, though this focus has widened recently regarding the role of the audience or the field surrounding the creative system. In the wider creativity research community a broader take is prevalent: the creative Person is considered as well as the environment or Press within which the creative entity operates in. Here we have the Four Ps of creativity: Person, Product, Process and Press. This paper presents the Four Ps, explaining each of the Four Ps in the context of creativity research and how it relates to computational creativity. To illustrate how useful the Four Ps can be in taking a fuller perspective on creativity, the concepts of novelty and value explored from each of the Four P perspectives, uncovering aspects that may otherwise be overlooked. This paper argues that the broader view of creativity afforded by the Four Ps is vital in guiding us towards more encompassing and comprehensive computational investigations of creativity.

One particular challenge in AI is the computational modelling and simulation of creativity. Feedback and learning from experience are key aspects of the creative process. Here we investigate how we could implement feedback in creative systems using a social model. From the field of creative writing we borrow the concept of a Writers Workshop as a model for learning through feedback. The Writers Workshop encourages examination, discussion and debates of a piece of creative work using a prescribed format of activities. We propose a computational model of the Writers Workshop as a roadmap for incorporation of feedback in artificial creativity systems. We argue that the Writers Workshop setting describes the anatomy of the creative process. We support our claim with a case study that describes how to implement the Writers Workshop model in a computational creativity system. We present this work using patterns other people can follow to implement similar designs in their own systems. We conclude by discussing the broader relevance of this model to other aspects of AI.

To what extent can we use social network activity to examine the value that electronic musicians place in each other's work? This talk reports on the work of the Valuing Electronic Music (VEM) project, documented online at http://valuingelectronicmusic.org. During the project we combined ethnographic observation and interviewing in London's electronic music scene with automated collection of quantitative data from the popular SoundCloud website. The talk at DMRN will reflect upon the findings of the research by the valuingelectronicmusic.org team, which have implications for our understanding and approximate measurement of the cultural value of electronic music. We shall also reflect on the challenges and rewards of combining situated qualitative research with quantitative analysis of large datasets gathered online, as well as our ongoing research and future plans. Social networking and new media websites have provided music makers with new spaces in which to negotiate and produce cultural value for their work, taking on tasks that would once have been the sphere of specialists in marketing, publicity and criticism. These phenomena appear to have had a particular impact on electronic music, which is typically made by lone, but highly networked, individuals and is often circulated non-commercially online, for example on http://www.soundcloud.com. We found that while certain kinds of activity on SoundCloud have little apparent economic value (e.g. commenting on each others' tracks, publishing free downloads) these activities seem to generate cultural value that facilitates more economically valuable work. For the most part, music-makers assert their concern for all listeners, but close attention to their activity (and how they describe it) suggests that interactions with peers (i.e. fellow music makers) are especially important for the production of value for their work. In conjunction with the findings from interviews with electronic musicians, we used computational analysis to study interactions in social networks. Through such analysis we extrapolated information about how musicians interact with each other on SoundCloud, and how they express appreciation of each other's work. Typically, it was more productive to study clusters of strongly connected cliques within the SoundCloud network, rather than a sample of the entire network. Using centrality measures such as PageRank or indegree analysis revealed little novel information beyond highlighting accounts representing artists that were very successful commercially; but the value of such artists' work was not prioritised by participants in our qualitative research. The SoundCloud user community tends to cluster according to several factors: for example we found empirical evidence of clusters forming around common musical genres, and also of clusters around certain geographical locations such as London which were privileged above others. Drawing from our existing findings, centred around the London music scene, we are currently applying similar quantitative analysis approaches to the Scottish electronic music scene. We hypothesise that such computational analysis of SoundCloud data will allow us to approximate the value placed on different electronic musicians' work, leading to a methodology to use social network analysis as a proxy for measuring certain types of musical value. Results of this ongoing work will be reported at DMRN. Our findings indicated a complex relationship between the two areas of work referred to as production (a blanket term covering all activities involved in the creation of an audio track) and DJing (combination of audio tracks into a continuous mix). Based on our existing work, we are planning future work to examine how DJs express value of producers' work through playing their tracks. The quantitative research centres around analysing how DJs play different tracks in their sets, including analysis of the contouring and dynamic shaping of a DJ set, detection of which tracks are played and what changes are made to the tracks. This will be supported by, and will in turn inform, qualitative research undertaken with DJs on how they choose music for their sets. Feedback on both the existing research findings and our future plans from DMRN will be welcome.

In this paper we present the Sharing Ancient WisdomS (SAWS) project. Working with wisdom texts, or gnomologia, the project aims to produce an enhanced digital scholarly edition of the collected manuscripts which both makes the Greek, Arabic and Spanish texts available and demonstrates the hypertexual nature of these texts. By positioning the texts as collections of sayings, of which a given manuscript only shows one narrative path, we demonstrate how a hypertextual approach allows us to explore alternate narrative paths within and across the texts and support researchers as they study the context, significance and transmission of the wisdoms within these works.

The Sharing Ancient Wisdoms project (SAWS) is establishing a research workflow of editing, linking and publishing semantically-enhanced TEI/XML-based digital editions of ancient manuscripts that contain wise sayings. Of particular research interest is the ability to investigate links between these manuscripts. Digital edition creation, storage, annotation and, most recently, the adding of RDF and Linked Data are hot topics in digital humanities research, making SAWS workflows and supporting technologies highly transferable. Updating and maintaining published files, currently stored in a web filestore, has become troublesome. Additionally, the lengthy, involved procedures of transcribing and editing manuscripts have caused delays. More intuitive interfaces for editing and annotating files would be helpful. Scholars studying manuscripts in right-to-left (RTL) languages have also reported difficulties working with standard XML editors. In this work we explore if SAWS's research workflows can be made more efficient and intuitive through the use of repository tools developed within Islandora for the Editing Modernism in Canada (EMiC) research project.

How is creativity manifested in improvisation? And how do musicians interpret music in a creative way? We have an intuitive understanding of the concept of creativity that we can use introspectively to suggest answers to these questions, both in theory and during performance. If, though, we want to program a computer to generate music in a creative way, the computer does not understand what creativity is. We cannot ask the computer to behave creatively unless we also give some definition of what such behaviour entails. So the problem becomes: how to define what musical creativity is to a computer. This work uses empirical methods borrowed from linguistics to capture the words which we strongly associate with creativity. An analysis of the language used in dictionary definitions and academic papers on creativity, as compared to everyday language use, has produced a list of words which we commonly use to discuss creativity, e.g. innovation, openness, divergent. Considering these words in the context of music improvisation and interpretation, I derive key attributes of creativity in this musical domain which can be used to guide an artificially intelligent musical system towards generating creative musical behaviour.

This thesis proposes SPECS: a Standardised Procedure for Evaluating Creative Systems. No methodology has been accepted as standard for evaluating the creativity of a system in the field of computational creativity and the multi-faceted and subjective nature of creativity generates substantial definitional issues. Evaluative practice has developed a general lack of rigour and systematicity, hindering research progress. SPECS is a standardised and systematic methodology for evaluating computational creativity. It is flexible enough to be applied to a variety of different types of creative system and adaptable to specific demands in different types of creativity. In the three-stage process of evaluation, researchers are required to be specific about what creativity entails in the domain they work in and what standards they test a system's creativity by. To assist researchers, definitional issues are investigated and a set of components representing aspects of creativity is presented, which was empirically derived using computational linguistics analysis. These components are recommended for use within SPECS, being offered as a general definition of creativity that can be customised to account for any specific priorities for creativity in a given domain. SPECS is applied in a case study for detailed comparisons of the creativity of three musical improvisation systems, identifying which systems are more creative than others and why. In a second case study, SPECS is used to capture initial impressions on the creativity of systems presented at a 2011 computational creativity research event. Five systems performing different creative tasks are compared and contrasted. These case studies exemplify the valuable information that can be obtained on a system's strengths and weaknesses. SPECS gives researchers vital feedback for improving their systems' creativity, informing further progress in computational creativity research.

Score Following is the process by which a musician can be tracked through their performance of a piece, for the purpose of accompanying the musician with the appropriate notes. This tracking is done by following the progress of the musician through the score (written music) of the piece, using observations of the notes they are playing. Artificially intelligent musical accompaniment is where a human musician is accompanied by a computer musician. The computer musician is able to produce musical accompaniment that relates musically to the human performance. Hidden Markov Models (HMMs) are a stochastic modelling tool that can be used to represent real-world systems in a variety of domains. This project discusses how HMMs can be used in the domain of Score Following and describes the construction and evaluation of a score following system that uses HMMs to implement score following. It explores the hypothesis that using an HMM to represent a musical score is an efficient and practical way to implement score following, and that in particular this method is suitable for providing real-time accompaniment to a human performer. The score followers developed during this project are tested and compared against other score following systems and against human musicians. The resulting performances support the project hypothesis to a large extent.

The SAWS ontology is our vocabulary for describing the types of relationships present between or within our texts. The ontology relationships themselves can be used to annotate manuscripts with these links. Technically, the SAWS ontology reuses and extends the FRBRoo model of bibliographic and cultural heritage information using the Erlangen OWL implementations.

A set of concepts which each contribute to the meaning of creativity. Each component/factor represents an aspect which is a constituent part of creative activity or thought. The full Collection of CreativityComponents is a collective definition of Creativity. Based on a SKOS organisation of knowledge. See Jordanous and Keller 2012 (Weaving Creativity into the Semantic Web) for further details.

Welcome to the website of the Sharing Ancient Wisdoms project, and the SAWS Dynamic Library of Wisdom Literatures. This project was funded by Humanities in the European Research Area, as part of their first Joint Research Programme. We are very grateful to them, and to our home institutions: King's College London, The Newman Institute Uppsala, and the University of Vienna. The SAWS Dynamic Library contains five main groups of texts. Elvira Wakelnig and colleagues in Vienna have made available two collections, Gnomological Material in Arabic and in Arabic-Spanish transmission, and Arabic Philosophical Compendia and Excerpts of Arabic and Latin Philosophical Texts; these include, among others, transcriptions of two abridgements of the ?iw?n al-?ikma, Ps.-??mir?'s Kit?b al-Sa??da, the first editions of three unpublished Arabic compilations of philosophical material, together with further excerpts from relevant texts, from Greek sources and from the Spanish Bocados di Oro whch drew on this tradition. Apophthegmata et gnomae secundum alphabetum comprises the first full edition of an important tradition of Greek gnomologia, arranged in alphabetical order, and edited from 16 manuscripts by Denis Searby and colleagues in Uppsala. A collection of Greek florilegia: Pinakes, prepared by Roueché and Searby, presents the tables of contents from three previously published Greek gnomologia, to give a further sense of the concerns characteristic of such assemblages. Kekaumenos, Consilia et Narrationes, is a new edition, by Charlotte Roueché, of an 11th century Greek text which is profoundly influenced by the tradtion of gnomologia. See a map of the manuscripts which we are publishing. The documents in the Dynamic Library can be consulted through the SAWS Folioscope. New users should take the Tour which the Folioscope offers, in order to ensure that they make the fullest possible use of all its features. The texts may be read separately or together. They can also be explored through the Indices in the Folioscope, and through the various visualisations. The XML of all the texts can be downloaded from the repository, and the schema for that XML is also available; the tools which have made this all possible, can be found under Methodology. To link to a particular document see How to cite, at the bottom of the Folioscope page; to link to a particular passage or line, use http://www.ancientwisdoms.ac.uk/folioscope/ followed by the Link ID. The full collection of machine readable citations can be found in the CTS inventory. All our work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License: see Creative Commons. All reuse or distribution of this work must contain somewhere a link back to the URL: http://ancientwisdoms.ac.uk/. This publication is open to all readers, who will use it for many reasons, with widely different expectations. We have attempted to make it as accessible as possible, particularly through the use of links to other resources, where readers can find further information if they choose to. In this we have been dependent on the reliable sources of information which are available online at the time of publication (summer 2013); we hope that the majority of such resources will remain available, and that many more will become accessible.

In music as in life, nothing is more important than people. Professional music-makers need audiences, and to reach those audiences, they need the support of many other people, from promoters and agents to fans who will rave about them to their friends. And artists of all kinds need contact with fellow artists: to inspire them, to collaborate with them, to compete with them, and simply to acknowledge them as peers. In isolation from people who value the music you value, it's hard to know how good you are, or how to take your work to the next level. As a recent report on the music industry put it, 'talent... cannot exist unless it is recognised by others in a network.' The Valuing Electronic Music project is an attempt to find out how this process of recognition happens in the digital age. We collected data on millions of user accounts on the SoundCloud website, focusing in particular on a random sample of 150 000. We also spoke to a range of people involved in London-based electronic music scenes (electronic music, followed by hip hop, being the kinds of music that are most represented on SoundCloud). Then we organised a public discussion between three electronic music-makers and an expert on electronic dance music, and interviewed writers, musicians, and promoters at the Convergence festival in London. These discussions enabled us to focus on the value of different kinds of relationships between music-makers and promoters, DJs, and other people involved in electronic music: for example, we found that music-makers may treat responses from live audiences and from well-informed listeners (including other music-makers) as more valuable than anonymous 'clicks' on a website. As we will discuss below, they may have good reasons for this preference, because people who are involved in a scene may be able to add more value to their music than people who are not, and websites such as SoundCloud may be more effective for cementing relationships with local audiences than for growing an international fanbase. You can listen in on some of the conversations we had via our website (http://www.valuingelectronicmusic.org/media). This is the project's main output, a 'public' report presenting key findings without technical jargon. It is founded on our peer-reviewed research (below) and was written in consultation with a panel of experts.

Digital distribution has greatly reduced the economic value of recorded music, and thus the potential for generating income through music. While this challenge to professional music-making has gathered pace, music production software has facilitated the creation of professional-sounding tracks in home studios. At the same time, social networking and new media websites have provided music makers with new spaces in which to negotiate and produce cultural value for their work, taking on tasks that would once have been the sphere of specialists in marketing, publicity and criticism. These phenomena appear to have had a particular impact on electronic music, which is typically made by lone, but highly networked, individuals and is often circulated non-commercially. Notwithstanding these developments, a record deal is still considered the mark of success and a reflection of a music-maker's value, and local, regional, national, and world-regional scenes remain important sites for the production of cultural value in music, with London being an unusually privileged location. For the most part, music-makers assert their concern for all listeners, but close attention to their activity (and how they describe it) suggests that interactions with peers are especially important for the production of value for their work. There is a complex relationship between the two areas of work referred to as production (a blanket term covering all activities involved in the creation of an audio track) and DJing (combination of audio tracks into a continuous mix): except in online venues, DJing tends to be better remunerated than production, yet production is accorded more cultural value than DJing; DJs play a significant role in the production of cultural value for producers, yet status as a DJ often depends on having cultural value as a producer. Live performance is vital to the production of both cultural and economic value, and there is evidence for exclusion from the production of value in terms of gender, location, and genre, where ethnicity and class may be implicated in the latter two.

Review of Machado, Romero and Greenfield (editors): Artificial intelligence and the arts Download a copy at https://rdcu.be/cPV33 (Shareable URL provided by publisher)

The Eighth International Conference on Computational Creativity (ICCC'17)1 was hosted at the Georgia Institute of Technology in Atlanta, Georgia, USA from June 19th - June 23rd, 2017. The ICCC'17 organising committee consisted of Ashok Goel (General Chair), Kazjon Grace (Workshop Co-chair), Matthew Guzdial (Media Chair), Mikhail Jacob (Local Chair), Anna Jordanous (Program Co-chair), Ruli Manurung (Workshop Co-chair) and Alison Pease (Program Co-chair). This report summarises the main topics addressed.

To learn about an emerging research area such as digital humanities (DH), why not get the people embedded at the heart of that research and its development to tell you about it? With this oral history of DH, "interviewees [are] trying to explain to those of us who weren't there how things really were" [1] (cited on p. 21 of this volume).

"What happens when algorithmic instructions are produced and given to dancers in real time and allow choreography to be created in front of an audience?" asks Sicchio (page 32). And what happens when hacker culture is incorporated into the mix? In live coding, the writing of code and its execution become a creative performance. Although live coding is typically associated with producing music in real time, Sicchio broadens the creative focus to incorporate physical movement and dance through improvised choreography. Building on previous work on algorithmic approaches to choreography and "live scoring" (real-time construction of choreographic instructions), Sicchio presents her practice-based research on computational approaches to improvised choreography under the common banner of "hacking choreography." The choreographic instructions resemble pseudocode and, unlike traditional choreography but like live coding, are sometimes projected as part of the performance. Sicchio focuses on how performances can be "hacked" to mimic the subversive circumventions and repurposing associated with computer hacking. She describes several methods of hacking choreography, including performer reinterpretation/ignoring of instructions, introduction of new instructions mid-performance, and (most intriguingly) employing feedback loops incorporating performer movement and sound projection, when the performer is working alongside sound. Although Sicchio assumes basic knowledge of choreographic terms and live coding, this is a fascinating read for anyone interested in coding as a performance or creative work. The paper is particularly timely in the context of the recently funded AHRC Live Code Research Network [1] of which Sicchio is a steering committee member. 1) Live Code Research Network, http://www.livecodenetwork.org/ (04/08/2015).

This is more of a computing text than the title suggests. The book explores the progress of artificial intelligence (AI) at modeling human intelligence. The author has a long history working within AI.

A key part of agile is the ability to handle change. This book exemplifies this principle, being a refocused second edition of Agile software engineering [1]. The book's central tenet is that "agility can be implemented anywhere." Hence the book now treats agile not just as a software engineering approach, but as a broader approach toward project management and development more generally. As a result, the book's content has been changed to discuss not just agile software engineering, but agile as "a lifestyle." These changes are done with some success, though at times the content seems artificially stretched to fit this new definition, and generally the authors could have included many more examples to illustrate their points.

PATTERNS OF INTUITION is a useful read about composers 'collaborating' with computational techniques in their musical work. It is an output of the POINT (Patterns Of INTuition) project, aimed at establishing 'creative dialogues' (p.2) with composers based on how their compositional styles can incorporate computational methods. A varied selection of composers are matched to an equally varied set of computational approaches to music-making, from spectral analysis to MIDI-based Markov models. The computational methods are typically drawn from current computer music research, with (for example) references to recent proceedings of the International Computer Music Conference (ICMC), the leading conference in this area.

Code for exploring the value of electronic music via analysing network interactions on Soundcloud.

An Islandora Solution pack for the DEFRA DTC archive project to allow users to create new Measurement objects (see DTC archive data model), upload CSV files to the DTC archive repository, check the validity of those CSV files against the DTC archive specified formats and generate RDF relating to the content of the CSV files.

Stylesheets generated for the Sharing Ancient Wisdoms project ( http://www.ancientwisdoms.ac.uk ). THe XSLT stylesheets use TEI/XML, RDF and a custom ontology based on CIDOC-CRM to generate models of information about relations between scholarly manuscripts

Can a computer evolve creative entities based on how creative they are? Taking the domain of jazz improvisation, this work investigates how creativity can be evolved and evaluated by a computational system. The aim is for the system to work with minimal human assistance, as autonomously as possible. The system employs a genetic algorithm to evolve musical parameters for algorithmic jazz music improvisation. For each set of parameters, several improvisations are generated. The fi?tness function of the genetic algorithm implements a set of criteria for creativity proposed by Graeme Ritchie. The evolution of the improvisation parameters is directed by the creativity demonstrated in the generated improvisations. From preliminary fi?ndings, whilst Ritchie's criteria does guide the system towards producing more acceptably pleasing and typical jazz music, the criteria (in their current form) rely too heavily on human intervention to be practically useful for computational evaluation of creativity. In pursuing more autonomous creativity assessment, however, this system is a promising testbed for examining alternative theories about how creativity could be evaluated computationally.

Code to take MIDI files of polyphonic music and split it up into its constituent voices, using strictly empirical methods (information on frequencies in context of a previous note). Using Matlab and the MIDI toolbox (included in this repository) by Petri Toiviainen and Tuomas Eerola, Department of Music, University of Jyväskylä, Finland: https://www.jyu.fi/hum/laitokset/musiikki/en/research/coe/materials/miditoolbox . This repository also contains the ICMC 2008 paper on this work and the corresponding PPT presentation.

Max/MSP code, documentation and technical reports (papers) for the HMM score follower reported in Jordanous (2007) MSc thesis, 2008 CIM paper and 2009 JNMR paper. The score follower uses hidden markov models to provide live automatic accompaniment (computer-generated) in live performance by a soloist, matching the soloist's tempo and expression, and following their position in the score.