Titlebook: Computational Creativity; The Philosophy and E Tony Veale,F. Amílcar Cardoso Book 2019 Springer Nature Switzerland AG 2019 Artificial Intel

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Evaluating Evaluation: Assessing Progress and Practices in Computational Creativity Research,s, 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 Syste

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Computer-Supported Human Creativity and Human-Supported Computer Creativity in Language,nts. Finally, we focus on human-supported computer creativity, where the burden of the creative process is mainly on the computer, while the human simply mediates the process during key steps whenever required. As an example modeling this type of creativity, we introduce HEADY-LINES, which automatic

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2509-6575 r the worlds of entertainment, culture, science, education, design, and art, in addition to artificial intelligence, and the book will be of value to practitioners and students in all these domains..978-3-319-43610-4Series ISSN 2509-6575 Series E-ISSN 2509-6583

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Systematizing Creativity: A Computational View,al Creativity (CC) is a recent but burgeoning area of creativity research that brings together academics and practitioners from diverse disciplines, genres and modalities, to explore the potential of our machines to be creative in their own right. As a scientific endeavor, CC proposes that computati

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A Framework for Description, Analysis and Comparison of Creative Systems,. A., The Creative Mind: Myths and Mechanisms, 2nd Ed., Routledge, London, 2004), by formalising the ideas she proposes. The aim is to move towards a model which allows detailed comparison, and hence better understanding, of systems, whether artificial, natural or hybrid, which exhibit behaviour whi

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Autonomous Intentionality in Computationally Creative Systems, by perceptions about the system and that perhaps the most difficult hurdles to overcome in this respect are those of system . and system .. We discuss ways in which these difficulties might be addressed and cite examples from the DARCI system that already exhibit these characteristics to some exten

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From Conceptual Mash-ups to Badass Blends: A Robust Computational Model of Conceptual Blending,with which we humans regularly understand and produce complex blends. While this facility will doubtless elude our best efforts at computational modeling for some time to come, there are practical forms of conceptual blending that are amenable to computational exploitation right now. In this chapter

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