Artificial Intelligence and Creativity: An Interdisciplinary ApproachT. Dartnall Creativity is one of the least understood aspects of intelligence and is often seen as `intuitive' and not susceptible to rational enquiry. Recently, however, there has been a resurgence of interest in the area, principally in artificial intelligence and cognitive science, but also in psychology, philosophy, computer science, logic, mathematics, sociology, and architecture and design. This volume brings this work together and provides an overview of this rapidly developing field. It addresses a range of issues. Can computers be creative? Can they help us to understand human creativity? How can artificial intelligence (AI) enhance human creativity? How, in particular, can it contribute to the `sciences of the artificial', such as design? Does the new wave of AI (connectionism, geneticism and artificial life) offer more promise in these areas than classical, symbol-handling AI? What would the implications be for AI and cognitive science if computers could not be creative? These issues are explored in five interrelated parts, each of which is introducted and explained by a leading figure in the field. - Prologue (Margaret Boden) - Part I: Foundational Issues (Terry Dartnall) - Part II: Creativity and Cognition (Graeme S. Halford and Robert Levinson) - Part III: Creativity and Connectionism (Chris Thornton) - Part IV: Creativity and Design (John Gero) - Part V: Human Creativity Enhancement (Ernest Edmonds) - Epilogue (Douglas Hofstadter) For researchers in AI, cognitive science, computer science, philosophy, psychology, mathematics, logic, sociology, and architecture and design; and anyone interested in the rapidly growing field of artificial intelligence and creativity. |
Other editions - View all
Artificial Intelligence and Creativity: An Interdisciplinary Approach T. Dartnall Limited preview - 2013 |
Artificial Intelligence and Creativity: An Interdisciplinary Approach T. Dartnall No preview available - 2010 |
Common terms and phrases
1994 Kluwer Academic abduction ability analogy answer architecture argument Artificial Intelligence back-propagation behaviour Boden Cambridge chess codelets cognitive science combination complex concepts conceptual space connectionism connectionist consider constraints construction context Copycat creative design creative process crossover Dartnall defined described design process design prototypes domain encoded evaluation evolution example explain exploration Fischer framework function genetic algorithms genetic operators Gero goal grammar human ideas indexing system input Intelligence and Creativity internal involves issues Karmiloff-Smith knowledge knowledge representation learning rules machine Machine Learning mapping mechanism memory metaphor method metonymic microprogramming mind Morph NETtalk neural networks neurons node notion novel operations output paradigm patterns philosophical predicate procedural knowledge procedures produce proof provides psychological random re-representation redescribe redescription relevant represent representation requires retrieval scientific semantics simulated annealing specific structure task tensor tensor product theory understanding University Press variables