Computational Creativity Theory
Research
Introduction
In order to progress as a science, Computational Creativity research needs more formalism in terms of how we evaluate progress in the software that we write. Such formalisms can involve assessment of the increase in value of the artefacts (paintings, compositions, poems, games, recipes, theorems, etc.) that are produced by software. Other formalisms can involve assessing how much creative responsibility a piece of software has, with the value of the artefacts produced being a secondary consideration. We are developing formal models of progress in Computational Creativity research which take into account both product and process, in addition to notions related to how people perceive software, and how software presents what it does and what it has produced.
Talks
Here are a couple of talks by Simon Colton in which he addressed some of the philosophical issues raised by the study of creative software:
Publications
Below are some of the papers from the group which give overviews of the field, and address issues of evaluation, accountability and other philosophical issues, in addition to suggesting some general approaches to Computational Creativity.
Cook, Michael; Colton, Simon Generating Code For Expressing Simple Preferences: Moving On From Hardcoding And Randomness Inproceedings In: Proceedings of the Sixth International Conference on Computational Creativity, pp. 8, 2015. @inproceedings{cook2015generating, title = {Generating Code For Expressing Simple Preferences: Moving On From Hardcoding And Randomness}, author = { Michael Cook and Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/cook_iccc2015.pdf}, year = {2015}, date = {2015-01-01}, booktitle = {Proceedings of the Sixth International Conference on Computational Creativity}, pages = {8}, abstract = {Software expressing intent and justifying creative decisions are important considerations when building systems in the context of Computational Creativity. However, getting software to express subjective opinions like simple preferences is difficult without mimicking existing people’s opinions or using random choice. In this paper, we propose an alternative way of enabling software to make meaningful decisions in smallscale subjective scenarios, such as choosing a favourite colour. Our system uses a combination of metrics as a fitness function for evolving short pieces of code that choose between artefacts. These ‘preference functions’ can make choices between simple items that are neither random nor based on an already existing opinion, and additionally have a sense of consistency. We describe the system, offer some example results from the work and suggest how this might lead to further developments in generative subjectivity in the future.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Software expressing intent and justifying creative decisions are important considerations when building systems in the context of Computational Creativity. However, getting software to express subjective opinions like simple preferences is difficult without mimicking existing people’s opinions or using random choice. In this paper, we propose an alternative way of enabling software to make meaningful decisions in smallscale subjective scenarios, such as choosing a favourite colour. Our system uses a combination of metrics as a fitness function for evolving short pieces of code that choose between artefacts. These ‘preference functions’ can make choices between simple items that are neither random nor based on an already existing opinion, and additionally have a sense of consistency. We describe the system, offer some example results from the work and suggest how this might lead to further developments in generative subjectivity in the future. |
Colton, Simon; Pease, Alison; Corneli, Joseph; Cook, Michael; Hepworth, Rose; Ventura, Dan Stakeholder Groups in Computational Creativity Research and Practice Incollection In: Computational Creativity Research: Towards Creative Machines, pp. 3–36, Springer, 2015. @incollection{colton2015stakeholder, title = {Stakeholder Groups in Computational Creativity Research and Practice}, author = { Simon Colton and Alison Pease and Joseph Corneli and Michael Cook and Rose Hepworth and Dan Ventura}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_ccchapter15.pdf}, year = {2015}, date = {2015-01-01}, booktitle = {Computational Creativity Research: Towards Creative Machines}, pages = {3--36}, publisher = {Springer}, abstract = {The notion that software could be independently and usefully creative is becoming more commonplace in scientific, cultural, business and public circles. It is not fanciful to imagine creative software embedded in society in the short to medium term, acting as collaborators and autonomous creative agents for much societal benefit. Technologically, there is still some way to go to enable Artificial Intelligence methods to create artefacts and ideas of value, and to get software to do so in interesting and engaging ways. There are also a number of sociological hurdles to overcome in getting society to accept software as being truly creative, and we concentrate on those here. We discuss the various communities that can be considered stakeholders in the perception of computers being creative or not. In particular, we look in detail at three sets of stakeholders, namely the general public, Computational Creativity researchers and fellow creatives.We put forward various philosophical points which we argue will shape the way in which society accepts creative software. We make various claims along the way about how people perceive software as being creative or not, which we believe should be addressed with scientific experimentation, and we call on the Computational Creativity research community to do just that.}, keywords = {}, pubstate = {published}, tppubtype = {incollection} } The notion that software could be independently and usefully creative is becoming more commonplace in scientific, cultural, business and public circles. It is not fanciful to imagine creative software embedded in society in the short to medium term, acting as collaborators and autonomous creative agents for much societal benefit. Technologically, there is still some way to go to enable Artificial Intelligence methods to create artefacts and ideas of value, and to get software to do so in interesting and engaging ways. There are also a number of sociological hurdles to overcome in getting society to accept software as being truly creative, and we concentrate on those here. We discuss the various communities that can be considered stakeholders in the perception of computers being creative or not. In particular, we look in detail at three sets of stakeholders, namely the general public, Computational Creativity researchers and fellow creatives.We put forward various philosophical points which we argue will shape the way in which society accepts creative software. We make various claims along the way about how people perceive software as being creative or not, which we believe should be addressed with scientific experimentation, and we call on the Computational Creativity research community to do just that. |
Colton, Simon; Cook, Michael; Hepworth, Rose; Pease, Alison On Acid Drops and Teardrops: Observer Issues in Computational Creativity Inproceedings In: Proceedings of the 7th AISB Symposium on Computing and Philosophy, 2014. @inproceedings{colton2014acid, title = {On Acid Drops and Teardrops: Observer Issues in Computational Creativity}, author = { Simon Colton and Michael Cook and Rose Hepworth and Alison Pease}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_aisb14c.pdf}, year = {2014}, date = {2014-01-01}, booktitle = {Proceedings of the 7th AISB Symposium on Computing and Philosophy}, abstract = {We argue that the notion of creativity in a person or software is a secondary and essentially contested concept. Hence, in Computational Creativity research – where we aim to build software taken seriously as independently creative – understanding the roles people take as process observer and product consumer is paramount. Depending on the domain, there can be a natural bias against software created artefacts, and Computational Creativity researchers have exacerbated this situation through Turing-style comparison tests. Framing this as a modified Chinese Room experiment, we propose two remedies to the situation. These involve software accounting for its decisions, actions and products, and taking the radical step of thinking of computer generated artefacts as fundamentally different to their human-produced counterparts. We use two case studies, where people interact with an automated painter and with computer-generated videogames, to highlight the observer issues we raise, and to demonstrate partial implementations of our remedies.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } We argue that the notion of creativity in a person or software is a secondary and essentially contested concept. Hence, in Computational Creativity research – where we aim to build software taken seriously as independently creative – understanding the roles people take as process observer and product consumer is paramount. Depending on the domain, there can be a natural bias against software created artefacts, and Computational Creativity researchers have exacerbated this situation through Turing-style comparison tests. Framing this as a modified Chinese Room experiment, we propose two remedies to the situation. These involve software accounting for its decisions, actions and products, and taking the radical step of thinking of computer generated artefacts as fundamentally different to their human-produced counterparts. We use two case studies, where people interact with an automated painter and with computer-generated videogames, to highlight the observer issues we raise, and to demonstrate partial implementations of our remedies. |
Colton, Simon; Pease, Alison; Corneli, Joseph; Cook, Michael; Llano, Maria Teresa Assessing Progress in Building Autonomously Creative Systems Inproceedings In: Proceedings of the Fifth International Conference on Computational Creativity, pp. 137–145, 2014. @inproceedings{colton2014assessing, title = {Assessing Progress in Building Autonomously Creative Systems}, author = { Simon Colton and Alison Pease and Joseph Corneli and Michael Cook and Maria Teresa Llano}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_iccc2014.pdf}, year = {2014}, date = {2014-01-01}, booktitle = {Proceedings of the Fifth International Conference on Computational Creativity}, pages = {137--145}, abstract = {Determining conclusively whether a new version of software creatively exceeds a previous version or a third party system is dicult, yet very important for scientific approaches in Computational Creativity research. We argue that software product and process need to be assessed simultaneously in assessing progress, and we introduce a diagrammatic formalism which exposes various timelines of creative acts in the construction and execution of successive versions of artefactgenerating software. The formalism enables estimations of progress or regress from system to system by comparing their diagrams and assessing changes in quality, quantity and variety of creative acts undertaken; audience perception of behaviours; and the quality of artefacts produced. We present a case study in the building of evolutionary art systems, and we use the formalism to highlight various issues in measuring progress in the building of creative systems.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Determining conclusively whether a new version of software creatively exceeds a previous version or a third party system is dicult, yet very important for scientific approaches in Computational Creativity research. We argue that software product and process need to be assessed simultaneously in assessing progress, and we introduce a diagrammatic formalism which exposes various timelines of creative acts in the construction and execution of successive versions of artefactgenerating software. The formalism enables estimations of progress or regress from system to system by comparing their diagrams and assessing changes in quality, quantity and variety of creative acts undertaken; audience perception of behaviours; and the quality of artefacts produced. We present a case study in the building of evolutionary art systems, and we use the formalism to highlight various issues in measuring progress in the building of creative systems. |
Pease, Alison; Colton, Simon; Ramezani, Ramin; Charnley, John; Reed, Kate A Discussion on Serendipity in Creative Systems Inproceedings In: Proceedings of the Fourth International Conference on Computational Creativity, pp. 64–71, 2013. @inproceedings{pease2013discussion, title = {A Discussion on Serendipity in Creative Systems}, author = { Alison Pease and Simon Colton and Ramin Ramezani and John Charnley and Kate Reed}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/pease_iccc13.pdf}, year = {2013}, date = {2013-01-01}, booktitle = {Proceedings of the Fourth International Conference on Computational Creativity}, pages = {64--71}, abstract = {We investigate serendipity, or happy, accidental discoveries, in CC, and propose computational concepts related to serendipity. These include a focus-shift, a breakdown of serendipitous discovery into prepared mind, serendipity trigger, bridge and result and three dimensions of serendipity: chance, sagacity and value. We propose a definition and standards for computational serendipity and evaluate three creative systems with respect to our standards. We argue that this is an important notion in creativity and, if carefully developed and used with caution, could result in a valuable new discovery technique in CC.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } We investigate serendipity, or happy, accidental discoveries, in CC, and propose computational concepts related to serendipity. These include a focus-shift, a breakdown of serendipitous discovery into prepared mind, serendipity trigger, bridge and result and three dimensions of serendipity: chance, sagacity and value. We propose a definition and standards for computational serendipity and evaluate three creative systems with respect to our standards. We argue that this is an important notion in creativity and, if carefully developed and used with caution, could result in a valuable new discovery technique in CC. |
Pease, Alison; Colton, Simon; Charnley, John The Turing Test and Computational Creativity Inproceedings In: Contributed talks proceedings of the Turing Centenary Conference, 2012. @inproceedings{Pease2012Turing, title = {The Turing Test and Computational Creativity}, author = {Alison Pease and Simon Colton and John Charnley}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/11/pease_tc12.pdf}, year = {2012}, date = {2012-11-01}, booktitle = {Contributed talks proceedings of the Turing Centenary Conference}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } |
Charnley, John; Pease, Alison; Colton, Simon On the Notion of Framing in Computational Creativity Inproceedings In: Proceedings of the Third International Conference on Computational Creativity, pp. 77–81, 2012. @inproceedings{charnley2012notion, title = {On the Notion of Framing in Computational Creativity}, author = { John Charnley and Alison Pease and Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/charnley_iccc12.pdf}, year = {2012}, date = {2012-01-01}, booktitle = {Proceedings of the Third International Conference on Computational Creativity}, pages = {77--81}, abstract = {In most domains, artefacts and the creativity that went into their production is judged within a context; where a context may include background information on how the creator feels about their work, what they think it expresses, how it fits in with other work done within their community, their mood before, during and after creation, and so on. We identify areas of framing information, such as motivation, intention, or the processes involved in creating a work, and consider how these areas might be applicable to the context of Computational Creativity. We suggest examples of how such framing information may be derived in existing creative systems and propose a novel dually-creative approach to framing, whereby an automated story generation system is employed, in tandem with the artefact generator, to produce suitable framing information. We outline how this method might be developed and some longer term goals.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } In most domains, artefacts and the creativity that went into their production is judged within a context; where a context may include background information on how the creator feels about their work, what they think it expresses, how it fits in with other work done within their community, their mood before, during and after creation, and so on. We identify areas of framing information, such as motivation, intention, or the processes involved in creating a work, and consider how these areas might be applicable to the context of Computational Creativity. We suggest examples of how such framing information may be derived in existing creative systems and propose a novel dually-creative approach to framing, whereby an automated story generation system is employed, in tandem with the artefact generator, to produce suitable framing information. We outline how this method might be developed and some longer term goals. |
Colton, Simon; Wiggins, Geraint A Computational Creativity: The Final Frontier? Inproceedings In: ECAI, pp. 21–26, 2012. @inproceedings{colton2012computational, title = {Computational Creativity: The Final Frontier?}, author = {Simon Colton and Geraint A Wiggins}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_ecai12.pdf}, year = {2012}, date = {2012-01-01}, booktitle = {ECAI}, volume = {12}, pages = {21--26}, abstract = {Notions relating to computational systems exhibiting creative behaviours have been explored since the very early days of computer science, and the field of Computational Creativity research has formed in the last dozen years to scientifically explore the potential of such systems. We describe this field via a working definition; a brief history of seminal work; an exploration of the main issues, technologies and ideas; and a look towards future directions. As a society, we are jealous of our creativity: creative people and their contributions to cultural progression are highly valued. Moreover, creative behaviour in people draws on a full set of intelligent abilities, so simulating such behaviour represents a serious technical challenge for Artificial Intelligence research. As such, we believe it is fair to characterise Computational Creativity as a frontier for AI research beyond all others—maybe, even, the final frontier.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Notions relating to computational systems exhibiting creative behaviours have been explored since the very early days of computer science, and the field of Computational Creativity research has formed in the last dozen years to scientifically explore the potential of such systems. We describe this field via a working definition; a brief history of seminal work; an exploration of the main issues, technologies and ideas; and a look towards future directions. As a society, we are jealous of our creativity: creative people and their contributions to cultural progression are highly valued. Moreover, creative behaviour in people draws on a full set of intelligent abilities, so simulating such behaviour represents a serious technical challenge for Artificial Intelligence research. As such, we believe it is fair to characterise Computational Creativity as a frontier for AI research beyond all others—maybe, even, the final frontier. |
Pease, Alison; Charnley, John; Colton, Simon Using Grounded Theory to Suggest Types of Framing Information for Computational Creativity Book Chapter In: Proceedings of the Workshop "Computational Creativity, Concept Invention, and General Intelligence", pp. 7–13, University of Osnabrück, Institute of Cognitive Science, 2012. @inbook{pease2012using, title = {Using Grounded Theory to Suggest Types of Framing Information for Computational Creativity}, author = { Alison Pease and John Charnley and Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/pease_c3g12.pdf}, year = {2012}, date = {2012-01-01}, booktitle = {Proceedings of the Workshop "Computational Creativity, Concept Invention, and General Intelligence"}, pages = {7--13}, publisher = {University of Osnabrück, Institute of Cognitive Science}, series = {PICS Publications of the Institute of Cognitive Science}, abstract = {In most domains, artefacts and the creativity that went into their production is judged within a context; where a context may include background information on how the creator feels about their work, what they think it expresses, how it fits in with other work done within their community, and so on. In some cases, such framing information may involve obfuscation in order to add mystery to the work or its creator, which can add to our perception of creativity.We describe a novel method for the analysis of human creativity, using grounded theory.We demonstrate the importance of grounded theory via an ethnographic study of interviews by John Tusa with contemporary artists. By exploring the type of context and background that the artists share, we have developed theories which highlight the importance of areas of framing information, such as motivation, intention, or the processes involved in creating a work. We extend this to consider the role of mystery and obfuscation in framing, by considering what artists do not say versus what is explicitly revealed.}, keywords = {}, pubstate = {published}, tppubtype = {inbook} } In most domains, artefacts and the creativity that went into their production is judged within a context; where a context may include background information on how the creator feels about their work, what they think it expresses, how it fits in with other work done within their community, and so on. In some cases, such framing information may involve obfuscation in order to add mystery to the work or its creator, which can add to our perception of creativity.We describe a novel method for the analysis of human creativity, using grounded theory.We demonstrate the importance of grounded theory via an ethnographic study of interviews by John Tusa with contemporary artists. By exploring the type of context and background that the artists share, we have developed theories which highlight the importance of areas of framing information, such as motivation, intention, or the processes involved in creating a work. We extend this to consider the role of mystery and obfuscation in framing, by considering what artists do not say versus what is explicitly revealed. |
Pease, Alison; Colton, Simon On Impact and Evaluation in Computational Creativity: A Discussion of the Turing Test and an Alternative Proposal Inproceedings In: Proceedings of the AISB symposium on AI and Philosophy, 2011. @inproceedings{pease2011impact, title = {On Impact and Evaluation in Computational Creativity: A Discussion of the Turing Test and an Alternative Proposal}, author = { Alison Pease and Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/pease_aisb11.pdf}, year = {2011}, date = {2011-01-01}, booktitle = {Proceedings of the AISB symposium on AI and Philosophy}, abstract = {Computational Creativity is the AI subfield in which we study how to build computational models of creative thought in science and the arts. From an engineering perspective, it is desirable to have concrete measures for assessing the progress made from one version of a program to another, or for comparing and contrasting different software systems for the same creative task. We describe the Turing Test and versions of it which have been used in order to measure progress in Computational Creativity. We show that the versions proposed thus far lack the important aspect of interaction, without which much of the power of the Turing Test is lost. We argue that the Turing Test is largely inappropriate for the purposes of evaluation in Computational Creativity, since it attempts to homogenize creativity into a single (human) style, does not take into account the importance of background and contextual information for a creative act, encourages superficial, uninteresting advances in front-ends, and rewards creativity which adheres to a certain style over that which creates something which is genuinely novel. We further argue that although there may be some place for Turing-style tests for Computational Creativity at some point in the future, it is currently untenable to apply any defensible version of the Turing Test. As an alternative to Turing-style tests, we introduce two descriptive models for evaluating creative software, the FACE model which describes creative acts performed by software in terms of tuples of generative acts, and the IDEA model which describes how such creative acts can have an impact upon an ideal audience, given ideal information about background knowledge and the software development process. While these models require further study and elaboration, we believe that they can be usefully applied to current systems as well as guiding further development of creative systems.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Computational Creativity is the AI subfield in which we study how to build computational models of creative thought in science and the arts. From an engineering perspective, it is desirable to have concrete measures for assessing the progress made from one version of a program to another, or for comparing and contrasting different software systems for the same creative task. We describe the Turing Test and versions of it which have been used in order to measure progress in Computational Creativity. We show that the versions proposed thus far lack the important aspect of interaction, without which much of the power of the Turing Test is lost. We argue that the Turing Test is largely inappropriate for the purposes of evaluation in Computational Creativity, since it attempts to homogenize creativity into a single (human) style, does not take into account the importance of background and contextual information for a creative act, encourages superficial, uninteresting advances in front-ends, and rewards creativity which adheres to a certain style over that which creates something which is genuinely novel. We further argue that although there may be some place for Turing-style tests for Computational Creativity at some point in the future, it is currently untenable to apply any defensible version of the Turing Test. As an alternative to Turing-style tests, we introduce two descriptive models for evaluating creative software, the FACE model which describes creative acts performed by software in terms of tuples of generative acts, and the IDEA model which describes how such creative acts can have an impact upon an ideal audience, given ideal information about background knowledge and the software development process. While these models require further study and elaboration, we believe that they can be usefully applied to current systems as well as guiding further development of creative systems. |
Pease, Alison; Colton, Simon Computational Creativity Theory: Inspirations Behind the FACE and the IDEA Models Inproceedings In: Proceedings of the Second International Conference on Computational Creativity, 2011. @inproceedings{pease2011computational, title = {Computational Creativity Theory: Inspirations Behind the FACE and the IDEA Models}, author = { Alison Pease and Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/pease_iccc11.pdf}, year = {2011}, date = {2011-01-01}, booktitle = {Proceedings of the Second International Conference on Computational Creativity}, abstract = {We introduce two descriptive models for evaluating creative software; the FACE model, which describes creative acts performed by software in terms of tuples of generative acts, and the IDEA model, which describes how such creative acts can have an impact upon an audience. We show how these models have been inspired both by ideas in the psychology of creativity and by an analysis of acts of human creativity.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } We introduce two descriptive models for evaluating creative software; the FACE model, which describes creative acts performed by software in terms of tuples of generative acts, and the IDEA model, which describes how such creative acts can have an impact upon an audience. We show how these models have been inspired both by ideas in the psychology of creativity and by an analysis of acts of human creativity. |
Colton, Simon; Pease, Alison; Charnley, John Computational Creativity Theory: The FACE and IDEA Descriptive Models Inproceedings In: Proceedings of the Second International Conference on Computational Creativity, pp. 90–95, 2011. @inproceedings{colton2011computational, title = {Computational Creativity Theory: The FACE and IDEA Descriptive Models}, author = { Simon Colton and Alison Pease and John Charnley}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_iccc11.pdf}, year = {2011}, date = {2011-01-01}, booktitle = {Proceedings of the Second International Conference on Computational Creativity}, pages = {90--95}, abstract = {We introduce computational creativity theory (CCT) as an analogue in computational creativity research to computational learning theory in machine learning. In its current draft, CCT comprises the FACE descriptive model of creative acts as tuples of generative acts, and the IDEA descriptive model of the impact such creative acts may have. To introduce these, we simplify various assumptions about software development, background material given to software, how creative acts are performed by computer, and how audiences consume the results. We use the two descriptive models to perform two comparisons studies, firstly for mathematical discovery software, and secondly for visual art generating programs. We conclude by discussing possible additions, improvements and refinements to CCT.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } We introduce computational creativity theory (CCT) as an analogue in computational creativity research to computational learning theory in machine learning. In its current draft, CCT comprises the FACE descriptive model of creative acts as tuples of generative acts, and the IDEA descriptive model of the impact such creative acts may have. To introduce these, we simplify various assumptions about software development, background material given to software, how creative acts are performed by computer, and how audiences consume the results. We use the two descriptive models to perform two comparisons studies, firstly for mathematical discovery software, and secondly for visual art generating programs. We conclude by discussing possible additions, improvements and refinements to CCT. |
Colton, Simon; de Mantaras, Ram'on L'opez; Stock, Oliviero Computational Creativity: Coming of Age Journal Article In: 2009. @article{colton2009computational, title = {Computational Creativity: Coming of Age}, author = { Simon Colton and Ram'on L'opez de Mantaras and Oliviero Stock}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_aimag09_editorial.pdf}, year = {2009}, date = {2009-01-01}, booktitle = {AI Magazine}, publisher = {AAAI Press}, abstract = {This editorial provides an introduction to current AI research on computationally created artifacts as well as to the papers and topics covered by this special issue on computational creativity.}, keywords = {}, pubstate = {published}, tppubtype = {article} } This editorial provides an introduction to current AI research on computationally created artifacts as well as to the papers and topics covered by this special issue on computational creativity. |
Pease, Alison; Smaill, Alan; Colton, Simon; Lee, John Bridging the Gap Between Argumentation Theory and the Philosophy of Mathematics Journal Article In: Foundations of Science, 14 (1-2), pp. 111–135, 2009. @article{pease2009bridging, title = {Bridging the Gap Between Argumentation Theory and the Philosophy of Mathematics}, author = { Alison Pease and Alan Smaill and Simon Colton and John Lee}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/pease_fos09.pdf}, year = {2009}, date = {2009-01-01}, journal = {Foundations of Science}, volume = {14}, number = {1-2}, pages = {111--135}, publisher = {Springer}, abstract = {We argue that there are mutually beneficial connections to be made between ideas in argumentation theory and the philosophy of mathematics, and that these connections can be suggested via the process of producing computational models of theories in these domains.We discuss Lakatos’s work (1976) in which he championed the informal nature of mathematics, and our computational representation of his theory. In particular, we outline our representation of Cauchy’s proof of Euler’s conjecture, which uses work by Haggith on argumentation structures, and identify connections between these structures and Lakatos’s methods.}, keywords = {}, pubstate = {published}, tppubtype = {article} } We argue that there are mutually beneficial connections to be made between ideas in argumentation theory and the philosophy of mathematics, and that these connections can be suggested via the process of producing computational models of theories in these domains.We discuss Lakatos’s work (1976) in which he championed the informal nature of mathematics, and our computational representation of his theory. In particular, we outline our representation of Cauchy’s proof of Euler’s conjecture, which uses work by Haggith on argumentation structures, and identify connections between these structures and Lakatos’s methods. |
Colton, Simon Seven Catchy Phrases for Computational Creativity Research Inproceedings In: Dagstuhl Seminar Proceedings, Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik 2009. @inproceedings{colton2009seven, title = {Seven Catchy Phrases for Computational Creativity Research}, author = { Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_dagstuhl09.pdf}, year = {2009}, date = {2009-01-01}, booktitle = {Dagstuhl Seminar Proceedings}, organization = {Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik}, abstract = {I understand that simulating creative processes by computer can enhance our understanding of creativity in humans. I also understand that there is more need than ever for software to help people to be more efficient in creative jobs. And I know that computational creativity research can be of great value in both these areas. However, Iʼm really only interested in the intellectual challenge of enabling nuts and bolts machines - bits and bytes computers - to create artefacts of real cultural value to society. Such behaviour used to be thought of as divinely inspired, no less than a gift from the Gods. This is why it is a worthy challenge for me to bet my career against. Building a truly computationally creative machine is as much a societal as a technical challenge, and it will need computational creativity researchers to come together in consensus about certain aspects of their field. To this end, I have written here seven phrases around which we could rally (or about which we could debate - which may also be healthy). I present the ideas from which the phrases emerged with little argumentation, in the tradition of a position paper. They are drawn from twelve years of immersion in the field of computational creativity during which Iʼve written an automated mathematician (HR) and an automated painter (The Painting Fool), and they have created artefacts which I believe are of real value to society.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } I understand that simulating creative processes by computer can enhance our understanding of creativity in humans. I also understand that there is more need than ever for software to help people to be more efficient in creative jobs. And I know that computational creativity research can be of great value in both these areas. However, Iʼm really only interested in the intellectual challenge of enabling nuts and bolts machines - bits and bytes computers - to create artefacts of real cultural value to society. Such behaviour used to be thought of as divinely inspired, no less than a gift from the Gods. This is why it is a worthy challenge for me to bet my career against. Building a truly computationally creative machine is as much a societal as a technical challenge, and it will need computational creativity researchers to come together in consensus about certain aspects of their field. To this end, I have written here seven phrases around which we could rally (or about which we could debate - which may also be healthy). I present the ideas from which the phrases emerged with little argumentation, in the tradition of a position paper. They are drawn from twelve years of immersion in the field of computational creativity during which Iʼve written an automated mathematician (HR) and an automated painter (The Painting Fool), and they have created artefacts which I believe are of real value to society. |
Colton, Simon Creativity Versus the Perception of Creativity in Computational Systems Inproceedings In: AAAI Spring Symposium: Creative Intelligent Systems, pp. 14–20, 2008. @inproceedings{colton2008creativity, title = {Creativity Versus the Perception of Creativity in Computational Systems}, author = { Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_aaai08symp.pdf}, year = {2008}, date = {2008-01-01}, booktitle = {AAAI Spring Symposium: Creative Intelligent Systems}, pages = {14--20}, abstract = {We add to the discussion of how to assess the creativity of programs which generate artefacts such as poems, theorems, paintings, melodies, etc. To do so, we first review some existing frameworks for assessing artefact generation programs. Then, drawing on our experience of building both a mathematical discovery system and an automated painter, we argue that it is not appropriate to base the assessment of a system on its output alone, and that the way it produces artefacts also needs to be taken into account. We suggest a simple framework within which the behaviour of a program can be categorised and described which may add to the perception of creativity in the system.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } We add to the discussion of how to assess the creativity of programs which generate artefacts such as poems, theorems, paintings, melodies, etc. To do so, we first review some existing frameworks for assessing artefact generation programs. Then, drawing on our experience of building both a mathematical discovery system and an automated painter, we argue that it is not appropriate to base the assessment of a system on its output alone, and that the way it produces artefacts also needs to be taken into account. We suggest a simple framework within which the behaviour of a program can be categorised and described which may add to the perception of creativity in the system. |
Colton, Simon Creative Logic Programming Inproceedings In: Proceedings of the 3rd. IJCAI Workshop on Creative Systems, pp. 77, 2003. @inproceedings{colton2003creative, title = {Creative Logic Programming}, author = { Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_ijcai03_creativity.pdf}, year = {2003}, date = {2003-01-01}, booktitle = {Proceedings of the 3rd. IJCAI Workshop on Creative Systems}, pages = {77}, abstract = {The standard machine learning paradigm is to find something that users know they are looking for, with the discovered artefact defined in terms of given background knowledge. We propose to extend this to automating the task of finding novel and interesting information – also based on the background knowledge – that the users do not knowthey are looking for. We sketch various methods for introducing knowledge to a knowledge base which are inspired by notions from the study of creativity. We attempt to determine situations where it is possible to project certain words from the creativity literature onto an agent (human, machine or otherwise), as it undertakes the task of adding information to a knowledge base. This study has enabled us to suggest a road-map for the development of creative logic programming systems, which extends inductive logic programming approaches to discovery tasks.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } The standard machine learning paradigm is to find something that users know they are looking for, with the discovered artefact defined in terms of given background knowledge. We propose to extend this to automating the task of finding novel and interesting information – also based on the background knowledge – that the users do not knowthey are looking for. We sketch various methods for introducing knowledge to a knowledge base which are inspired by notions from the study of creativity. We attempt to determine situations where it is possible to project certain words from the creativity literature onto an agent (human, machine or otherwise), as it undertakes the task of adding information to a knowledge base. This study has enabled us to suggest a road-map for the development of creative logic programming systems, which extends inductive logic programming approaches to discovery tasks. |
Pease, Alison; Colton, Simon; Smaill, Alan; Lee, John Lakatos and Machine Creativity Inproceedings In: Second Workshop on Creative Systems, Approaches to Creativity in Artificial Intelligence and Cognitive Science at the European Conference on Artificial Intelligence (ECAI 2002), 2002. @inproceedings{pease2002lakatos, title = {Lakatos and Machine Creativity}, author = { Alison Pease and Simon Colton and Alan Smaill and John Lee}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/pease_ecai02workshop.pdf}, year = {2002}, date = {2002-01-01}, booktitle = {Second Workshop on Creative Systems, Approaches to Creativity in Artificial Intelligence and Cognitive Science at the European Conference on Artificial Intelligence (ECAI 2002)}, abstract = {We argue that Lakatos’ work on the history and philosophy of mathematics is of key relevance to machine creativity as it suggests ways in which to explore and transform concept spaces, rerepresent knowledge and change evaluation criteria. We describe approaches to implementing methods which Lakatos identifies, including our own approach, which extends Colton’s HR and has enabled us to automatically generate mathematical conjectures, concepts and examples which were previously impossible in HR - including Goldbach’s conjecture. The methods are of general importance as they can be applied to many domains - we describe their theoretical application to game plans, two-dimensional geometry, moral philosophy, philosophy of mind, political argument and meta-level reasoning.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } We argue that Lakatos’ work on the history and philosophy of mathematics is of key relevance to machine creativity as it suggests ways in which to explore and transform concept spaces, rerepresent knowledge and change evaluation criteria. We describe approaches to implementing methods which Lakatos identifies, including our own approach, which extends Colton’s HR and has enabled us to automatically generate mathematical conjectures, concepts and examples which were previously impossible in HR - including Goldbach’s conjecture. The methods are of general importance as they can be applied to many domains - we describe their theoretical application to game plans, two-dimensional geometry, moral philosophy, philosophy of mind, political argument and meta-level reasoning. |
Colton, Simon; Pease, Alison; Ritchie, Graeme The Effect of Input Knowledge on Creativity Inproceedings In: Proceedings of the ICCBR'01 Workshop on Creative Systems, 2001. @inproceedings{colton2001effect, title = {The Effect of Input Knowledge on Creativity}, author = { Simon Colton and Alison Pease and Graeme Ritchie}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_iccbr01.pdf}, year = {2001}, date = {2001-01-01}, booktitle = {Proceedings of the ICCBR'01 Workshop on Creative Systems}, abstract = {Recently, many programs have been written to perform tasks which are usually regarded as requiring creativity in humans. We can derive some commonalities between these programs in order to build further creative programs. Key to this is the derivation of certain measures which assess how creative a program is. Starting from recent proposals by Ritchie, we define possible measures which describe the extent to which a program produces novel output. We discuss how this relates to the creativity of the program.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } Recently, many programs have been written to perform tasks which are usually regarded as requiring creativity in humans. We can derive some commonalities between these programs in order to build further creative programs. Key to this is the derivation of certain measures which assess how creative a program is. Starting from recent proposals by Ritchie, we define possible measures which describe the extent to which a program produces novel output. We discuss how this relates to the creativity of the program. |
Pease, Alison; Winterstein, Daniel; Colton, Simon Evaluating Machine Creativity Inproceedings In: Workshop on Creative Systems, 4th International Conference on Case Based Reasoning, pp. 129–137, 2001. @inproceedings{pease2001evaluating, title = {Evaluating Machine Creativity}, author = { Alison Pease and Daniel Winterstein and Simon Colton}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/pease_iccbr01.pdf}, year = {2001}, date = {2001-01-01}, booktitle = {Workshop on Creative Systems, 4th International Conference on Case Based Reasoning}, pages = {129--137}, abstract = {We consider relevant aspects of evaluating creativity to be input, output and the process by which the output is achieved. These issues may be further divided, and we highlight associated justifications and controversies. Appropriate methods of measuring these aspects are suggested and discussed.}, keywords = {}, pubstate = {published}, tppubtype = {inproceedings} } We consider relevant aspects of evaluating creativity to be input, output and the process by which the output is achieved. These issues may be further divided, and we highlight associated justifications and controversies. Appropriate methods of measuring these aspects are suggested and discussed. |
Colton, Simon; Steel, Graham Artificial Intelligence and Scientific Creativity Journal Article In: Artificial Intelligence and the Study of Behaviour Quarterly, 102 , 1999. @article{colton1999artificial, title = {Artificial Intelligence and Scientific Creativity}, author = { Simon Colton and Graham Steel}, url = {http://ccg.doc.gold.ac.uk/wp-content/uploads/2016/10/colton_aisbq99.pdf}, year = {1999}, date = {1999-01-01}, journal = {Artificial Intelligence and the Study of Behaviour Quarterly}, volume = {102}, keywords = {}, pubstate = {published}, tppubtype = {article} } |