Modelling High Level Cognitive Processes

This book is a practical guide to building computational models of high-level cognitive processes and systems. High-level processes are those central cognitive processes involved in thinking, reasoning, planning, and so on. These processes appear to share representational and processing requirements, and it is for this reason that they are considered together in this text. The book is divided into three parts. Part I considers foundational and background issues. Part II provides a series of case studies spanning a range of cognitive domains. Part III reflects upon issues raised by the case studies. Teachers of cognitive modeling may use material from Part I to structure lectures and practical sessions, with chapters in Part II forming the basis of in-depth student projects. All models discussed in this book are developed within the COGENT environments. COGENT provides a graphical interface in which models may be sketched as "box and arrow" diagrams and is both a useful teaching tool and a productive research tool. As such, this book is designed to be of use to both students of cognitive modeling and active researchers. For students, the book provides essential background material plus an extensive set of example models, exercises and project material. Researchers of both symbolic and connectionist persuasions will find the book of interest for its approach to cognitive modeling, which emphasizes methodological issues. They will also find that the COGENT environment itself has much to offer.

This book is a practical guide to building computational models of high-level cognitive processes and systems. High-level processes are those central cognitive processes involved in thinking, reasoning, planning, and so on. These processes appear to share representational and processing requirements, and it is for this reason that they are considered together in this text. The book is divided into three parts. Part I considers foundational and background issues. Part II provides a series of case studies spanning a range of cognitive domains. Part III reflects upon issues raised by the case studies. Teachers of cognitive modeling may use material from Part I to structure lectures and practical sessions, with chapters in Part II forming the basis of in-depth student projects. All models discussed in this book are developed within the COGENT environments. COGENT provides a graphical interface in which models may be sketched as "box and arrow" diagrams and is both a useful teaching tool and a productive research tool. As such, this book is designed to be of use to both students of cognitive modeling and active researchers. For students, the book provides essential background material plus an extensive set of example models, exercises and project material. Researchers of both symbolic and connectionist persuasions will find the book of interest for its approach to cognitive modeling, which emphasizes methodological issues. They will also find that the COGENT environment itself has much to offer.

"A broad introductory treatment of cognitive modeling for students and researchers who want an accessible primer"--

This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including those for ownership of actions, fear and dreaming, the integration of emotions in joint decision-making based on empathic understanding, and evolving social networks – illustrate the potential of the approach. Dedicated software is available to support building models in a conceptual or graphical manner, transforming them into an executable format and performing simulation experiments. The majority of the material presented has been used and positively evaluated by undergraduate and graduate students and researchers in the cognitive, social and AI domains. Given its detailed coverage, the book is ideally suited as an introduction for graduate and undergraduate students in many different multidisciplinary fields involving cognitive, affective, social, biological, and neuroscience domains.

Connectionism is a way of modelling how the brain uses streams of sensory inputs to understand the world and produce behaviour, based on cognitive processes which actually occur. This book describes the principles, and their application to explaining how the brain produces speech, forms memories and recognises faces, how intellect develops, and how it deteriorates after brain damage. Part I explores the basic concepts, the architecture and properties of the most common connectionist models, and how connectionist learning rules work. Part II describes and evaluates connectionist models of a variety of cognitive processes, including the learning and production of speech, the formation of episodic memories and visual representations, the development of cognitive processes in infancy, and their breakdown in brain-damaged patients. The models range from some well-known classics to others at the frontiers of current research. Each chapter ends with a list of recommended further reading. Also included is a disk with the software for running tlearn, a user-friendly simulator for connectionist modelling of cognitive processes, which will run on either PCs or Macs. The software includes exercises to introduce the simulator, and working copies to explore some of the models described in the text. A reference handbook for tlearn is included to enable readers to build their own models. The authors, as well as being leading researchers in their field, have extensive experienceof teaching connectionism to undergraduates. They have written the first comprehensive, up-to-date textbook on connectionist modelling, designed specifically for advanced undergraduates, and accessible to those with only limited knowledge of mathematics. This will be an essential introductory text for all students in psychology or cognitive science taking a course on connectionism.

Computational Models of Cognitive Processes collects refereed versions of papers presented at the 13th Neural Computation and Psychology Workshop (NCPW13) that took place July 2012, in San Sebastian (Spain). This workshop series is a well-established and unique forum that brings together researchers from such diverse disciplines as artificial intelligence, cognitive science, computer science, neurobiology, philosophy and psychology to discuss their latest work on models of cognitive processes. Contents:Language:Modelling Language — Vision Interactions in the Hub and Spoke Framework (A C Smith, P Monaghan and F Huettig)Modelling Letter Perception: The Effect of Supervision and Top-Down Information on Simulated Reaction Times (M Klein, S Frank, S Madec and J Grainger)Encoding Words into a Potts Attractor Network (S Pirmoradian and A Treves)Unexpected Predictability in the Hawaiian Passive (Ō Parker Jones and J Mayor)Difference Between Spoken and Written Language Based on Zipf's Law Analysis (J S Kim, C Y Lee and B T Zhang)Reading Aloud is Quicker than Reading Silently: A Study in the Japanese Language Demonstrating the Enhancement of Cognitive Processing by Action (H-F Yanai, T Konno and A Enjyoji)Development:Testing a Dynamic Neural Field Model of Children's Category Labelling (K E Twomey and J S Horst)Theoretical and Computational Limitations in Simulating 3- to 4-Month-Old Infants' Categorization Processes (M Mermillod, N Vermeulen, G Kaminsky, E Gentaz and P Bonin)Reinforcement-Modulated Self-Organization in Infant Motor Speech Learning (A S Warlaumont)A Computational Model of the Headturn Preference Procedure: Design, Challenges, and Insights (C Bergmann, L Ten Bosch and L Boves)Right Otitis Media in Early Childhood and Language Development: An ERP Study (M F Alonso, P Uclés and P Saz)High-Level Cognition:The Influence of Implementation on “Hub” Models of Semantic Cognition (O Guest, R P Cooper and E J Davelaar)Hierarchical Structure in Prefrontal Cortex Improves Performance at Abstract Tasks (R Tukker, A C Van Rossum, S Frank and W F G Haselager)Interactive Activation Networks for Modelling Problem Solving (P Monaghan, T Ormerod and U N Sio)On Observational Learning of Hierarchies in Sequential Tasks: A Dynamic Neural Field Model (E Sousa, W Erlhagen and E Bicho)Knowing When to Quit on Unlearnable Problems: Another Step Towards Autonomous Learning (T R Shultz and E Doty)A Conflict/Control-Loop Hypothesis of Hemispheric Brain Reserve Capacity (N Rendell and E J Davelaar)Action and Emotion:Modeling the Actor-Critic Architecture by Combining Recent Work in Reservoir Computing and Temporal Difference Learning in Complex Environments (J J Rodny and D C Noelle)The Conceptualisation of Emotion Qualia: Semantic Clustering of Emotional Tweets (E Y Bann and J J Bryson)A Neuro-Computational Study of Laughter (M F Alonso, P Loste, J Navarro, R Del Moral, R Lahoz-Beltra and P C Marijuán) Readership: Students and researchers in biocybernetics, neuroscience, cognitive science, psychology and artificial intelligence and those interested in neural models of psychological phenomena. Keywords:Cognitive Science;Computational Modeling;Psychology;Neural NetworksKey Features:An invaluable resource for researchers interested in neural models of psychological phenomenaEnables readers to catch up with a fast moving discipline by reading contributions that are typically published as journal articles only a couple of years laterOffers an overview of current computational models of cognitive processes in a single bookChapters are written by world-leading experts in the field

The emerging interdisciplinary field of cognitive choice models integrates theory and recent research findings from both decision process and choice behavior. Cognitive decision processes provide the interface between the environment and brain, enabling choice behavior, and the basic cognitive mechanisms underlying decision processes are fundamental to all fields of human activity. Yet cognitive processes and choice processes are often studied separately, whether by decision theorists, consumer researchers, or social scientists. In Cognitive Choice Modeling, Zheng Joyce Wang and Jerome R. Busemeyer introduce a new cognitive modeling approach to the study of human choice behavior. Integrating recent research findings from both cognitive science and choice behavior, they lay the groundwork for the emerging interdisciplinary field of cognitive choice modeling.

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.