Computational and Cognitive Models of Creative Design VI
| Author | : John Steven Gero |
| Publisher | : Key Centre of Design Comp & Cogntn |
| Total Pages | : 385 |
| Release | : 2005 |
| Genre | : Art |
| ISBN | : 1864877898 |
Computational And Cognitive Models Of Creative Design Vi
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Design Computing and Cognition’22
| Author | : John S Gero |
| Publisher | : Springer Nature |
| Total Pages | : 819 |
| Release | : 2023-01-04 |
| Genre | : Technology & Engineering |
| ISBN | : 3031204182 |
This book reports research and development that represent the state of the art in artificial intelligence in design, design cognition, design neurocognition, and design theories from the Tenth International Conference on Design Computing and Cognition held in Glasgow, UK, in 2022. The 48 chapters are grouped under the headings of natural language processing and design; design cognition; design neurocognition; learning and design; creative design and co-design; shape grammars; quantum computing; and human behavior. These contributions are of particular interest to design researchers and design educators, as well as to users of advanced computation and cognitive science. This book contains knowledge about the cognitive and neurocognitive behavior of designers, which is valuable to those who need to gain a better understanding of designing.
Cognitive Systems
| Author | : Chris Forsythe |
| Publisher | : Psychology Press |
| Total Pages | : 325 |
| Release | : 2006-08-15 |
| Genre | : Computers |
| ISBN | : 1135605386 |
The leading thinkers from the cognitive science tradition participated in a workshop sponsored by Sandia National Laboratories in July of 2003 to discuss progress in building their models. The goal was to summarize the theoretical and empirical bases for cognitive systems and to present exemplary developments in the field. Following the workshop, a great deal of planning went into the creation of this book. Eleven of the twenty-six presenters were asked to contribute chapters, and four chapters are the product of the breakout sessions in which critical topics were discussed among the participants. An introductory chapter provides the context for this compilation. Cognitive Systems thus presents a unique merger of cognitive modeling and intelligent systems, and attempts to overcome many of the problems inherent in current expert systems. It will be of interest to researchers and students in the fields of cognitive science, computational modeling, intelligent systems, artificial intelligence, and human-computer interaction.
Computational Creativity
| Author | : Tony Veale |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2019-08-07 |
| Genre | : Computers |
| ISBN | : 9783319436081 |
Computational creativity is an emerging field of research within AI that focuses on the capacity of machines to both generate and evaluate novel outputs that would, if produced by a human, be considered creative. This book is intended to be a canonical text for this new discipline, through which researchers and students can absorb the philosophy of the field and learn its methods. After a comprehensive introduction to the idea of systematizing creativity the contributions address topics such as autonomous intentionality, conceptual blending, literature mining, computational design, models of novelty, evaluating progress in related research, computer-supported human creativity and human-supported computer creativity, common-sense knowledge, and models of social creativity. Products of this research will have real consequences for 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.
Integrated Models of Cognitive Systems
| Author | : Wayne D. Gray |
| Publisher | : Oxford University Press |
| Total Pages | : 496 |
| Release | : 2007-04-19 |
| Genre | : Psychology |
| ISBN | : 0198040776 |
The field of cognitive modeling has progressed beyond modeling cognition in the context of simple laboratory tasks and begun to attack the problem of modeling it in more complex, realistic environments, such as those studied by researchers in the field of human factors. The problems that the cognitive modeling community is tackling focus on modeling certain problems of communication and control that arise when integrating with the external environment factors such as implicit and explicit knowledge, emotion, cognition, and the cognitive system. These problems must be solved in order to produce integrated cognitive models of moderately complex tasks. Architectures of cognition in these tasks focus on the control of a central system, which includes control of the central processor itself, initiation of functional processes, such as visual search and memory retrieval, and harvesting the results of these functional processes. Because the control of the central system is conceptually different from the internal control required by individual functional processes, a complete architecture of cognition must incorporate two types of theories of control: Type 1 theories of the structure, functionality, and operation of the controller, and type 2 theories of the internal control of functional processes, including how and what they communicate to the controller. This book presents the current state of the art for both types of theories, as well as contrasts among current approaches to human-performance models. It will be an important resource for professional and student researchers in cognitive science, cognitive-engineering, and human-factors. Contributors: Kevin A. Gluck, Jerry T. Ball, Michael A. Krusmark, Richard W. Pew, Chris R. Sims, Vladislav D. Veksler, John R. Anderson, Ron Sun, Nicholas L. Cassimatis, Randy J. Brou, Andrew D. Egerton, Stephanie M. Doane, Christopher W. Myers, Hansjörg Neth, Jeremy M Wolfe, Marc Pomplun, Ronald A. Rensink, Hansjörg Neth, Chris R. Sims, Peter M. Todd, Lael J. Schooler, Wai-Tat Fu, Michael C. Mozer, Sachiko Kinoshita, Michael Shettel, Alex Kirlik, Vladislav D. Veksler, Michael J. Schoelles, Jerome R. Busemeyer, Eric Dimperio, Ryan K. Jessup, Jonathan Gratch, Stacy Marsella, Glenn Gunzelmann, Kevin A. Gluck, Scott Price, Hans P. A. Van Dongen, David F. Dinges, Frank E. Ritter, Andrew L. Reifers, Laura Cousino Klein, Michael J. Schoelles, Eva Hudlicka, Hansjörg Neth, Christopher W. Myers, Dana Ballard, Nathan Sprague, Laurence T. Maloney, Julia Trommershäuser, Michael S. Landy, A. Hornof, Michael J. Schoelles, David Kieras, Dario D. Salvucci, Niels Taatgen, Erik M. Altmann, Richard A. Carlson, Andrew Howes, Richard L. Lewis, Alonso Vera, Richard P. Cooper, and Michael D. Byrne
Models and Cognition
| Author | : Jonathan A. Waskan |
| Publisher | : MIT Press |
| Total Pages | : 341 |
| Release | : 2012-01-13 |
| Genre | : Philosophy |
| ISBN | : 0262293226 |
A groundbreaking argument challenging the traditional linguistic representational model of cognition proposes that representational states should be conceptualized as the cognitive equivalent of scale models. In this groundbreaking book, Jonathan Waskan challenges cognitive science's dominant model of mental representation and proposes a novel, well-devised alternative. The traditional view in the cognitive sciences uses a linguistic (propositional) model of mental representation. This logic-based model of cognition informs and constrains both the classical tradition of artificial intelligence and modeling in the connectionist tradition. It falls short, however, when confronted by the frame problem—the lack of a principled way to determine which features of a representation must be updated when new information becomes available. Proposed alternatives, including the imagistic model, have not so far resolved this problem. Waskan proposes instead the Intrinsic Cognitive Models (ICM) hypothesis, which argues that representational states can be conceptualized as the cognitive equivalent of scale models. Waskan argues further that the proposal that humans harbor and manipulate these cognitive counterparts to scale models offers the only viable explanation for what most clearly differentiates humans from other creatures: their capacity to engage in truth-preserving manipulation of representations.
Cognition and the Creative Machine
| Author | : Ana-Maria Oltețeanu |
| Publisher | : Springer Nature |
| Total Pages | : 282 |
| Release | : 2020-05-23 |
| Genre | : Computers |
| ISBN | : 3030303225 |
How would you assemble a machine that can be creative, what would its cogs be? Starting from how humans do creative problem solving, the author has developed a framework to explore whether a diverse set of creative problem-solving tasks can be solved computationally using a unified set of principles. In this book she describes the implementation of related prototype AI systems, and the computational and empirical experiments conducted. The book will be of interest to researchers, graduate students, and laypeople engaged with ideas in artificial intelligence, cognitive science, and creativity.
Computational Modeling in Cognition
| Author | : Stephan Lewandowsky |
| Publisher | : SAGE Publications |
| Total Pages | : 377 |
| Release | : 2010-11-29 |
| Genre | : Psychology |
| ISBN | : 1452223386 |
An accessible introduction to the principles of computational and mathematical modeling in psychology and cognitive science This practical and readable work provides students and researchers, who are new to cognitive modeling, with the background and core knowledge they need to interpret published reports, and develop and apply models of their own. The book is structured to help readers understand the logic of individual component techniques and their relationships to each other.
Computational Models for Cognitive Vision
| Author | : Hiranmay Ghosh |
| Publisher | : John Wiley & Sons |
| Total Pages | : 240 |
| Release | : 2020-07-01 |
| Genre | : Computers |
| ISBN | : 1119527899 |
Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author’s ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as “artificial intelligence”. The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: · knowledge representation techniques · evolution of cognitive architectures · deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.
Computational Modeling of Cognition and Behavior
| Author | : Simon Farrell |
| Publisher | : Cambridge University Press |
| Total Pages | : 485 |
| Release | : 2018-02-22 |
| Genre | : Psychology |
| ISBN | : 1108547141 |
Computational modeling is now ubiquitous in psychology, and researchers who are not modelers may find it increasingly difficult to follow the theoretical developments in their field. This book presents an integrated framework for the development and application of models in psychology and related disciplines. Researchers and students are given the knowledge and tools to interpret models published in their area, as well as to develop, fit, and test their own models. Both the development of models and key features of any model are covered, as are the applications of models in a variety of domains across the behavioural sciences. A number of chapters are devoted to fitting models using maximum likelihood and Bayesian estimation, including fitting hierarchical and mixture models. Model comparison is described as a core philosophy of scientific inference, and the use of models to understand theories and advance scientific discourse is explained.
