In this work, a broad, generic computational model was developed that instantiates Dr. Sun's framework and enables the testing of his theoretical approach in a variety of ways. With this model, simulation results were matched with data of human cognition in a variety of different domains. Formal (mathematical and computational) analyses were also carried out to further explore the model and its numerous implementational details. Furthermore, this book addresses some of the most significant theoretical issues, such as symbol grounding, intentionality, social cognition, consciousness, and other theoretical issues in relation to the framework. The general framework and the model developed generate interesting insights into these theoretical issues.
Research in the cognitive sciences has advanced significantly in recent decades. Computational cognitive modeling has profoundly changed the ways in which we understand cognition. Empirical research has progressed as well, offering new insights into many psychological phenomena. This book investigates the possibility of exploiting the successes of the cognitive sciences to establish a better foundation for the social sciences, including the disciplines of sociology, anthropology, economics, and political science. The result may be a new, powerful, integrative intellectual enterprise: the cognitive social sciences.
The book treats a range of topics selected to capture issues that arise across the social sciences, covering computational, empirical, and theoretical approaches. The chapters, by leading scholars in both the cognitive and the social sciences, explore the relationship between cognition and society, including such issues as methodologies of studying cultural differences; the psychological basis of politics (for instance, the role of emotion and the psychology of moral choices); cognitive dimensions of religion; cognitive approaches to economics; meta-theoretical questions on the possibility of the unification of social and cognitive sciences. Combining depth and breadth, the book encourages fruitful interdisciplinary interaction across many fields.
The 26 revised full papers presented together with an introductory overview by the volume editors have been through a twofold process of careful reviewing and revision. The papers are organized in the following topical sections: structured connectionism and rule representation; distributed neural architectures and language processing; transformation and explanation; robotics, vision, and cognitive approaches.
This book is the outgrowth of The IJCAI Workshop on Connectionist-Symbolic Integration: From Unified to Hybrid Approaches, held in conjunction with the fourteenth International Joint Conference on Artificial Intelligence (IJCAI '95). Featuring various presentations and discussions, this two-day workshop brought to light many new ideas, controversies, and syntheses which lead to the present volume.
This book is concerned with the development, analysis, and application of hybrid connectionist-symbolic models in artificial intelligence and cognitive science. Drawing contributions from a large international group of experts, it describes and compares a variety of models in this area. The types of models discussed cover a wide range of the evolving spectrum of hybrid models, thus serving as a well-balanced progress report on the state of the art. As such, this volume provides an information clearinghouse for various proposed approaches and models that share the common belief that connectionist and symbolic models can be usefully combined and integrated, and such integration may lead to significant advances in understanding intelligence.