Perspectives in Neural Computing Connectionist Models of Learning, Development and Evolution

Presents neural network modelling in the areas of evolution, learning, and development. This book, organized in six sections, covers the neural basis of cognition; development and category learning; implicit learning; social cognition; and, semantics. It also covers artificial intelligence, mathematics, psychology, neurobiology, and philosophy. Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Psychology Workshop - the only international workshop devoted to connectionist models of psychological phenomena. With a main theme of neural network modelling in the areas of evolution, learning, and development, the papers are organized into six sections: The neural basis of cognition Development and category learning Implicit learning Social cognition Evolution Semantics Covering artificial intelligence, mathematics, psychology, neurobiology, and philosophy, it will be an invaluable reference work for researchers and students working on connectionist modelling in computer science and psychology, or in any area related to cognitive science.

Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Psychology Workshop - the only international workshop devoted to connectionist models of psychological phenomena. With a main theme of neural network modelling in the areas of evolution, learning, and development, the papers are organized into six sections: The neural basis of cognition Development and category learning Implicit learning Social cognition Evolution Semantics Covering artificial intelligence, mathematics, psychology, neurobiology, and philosophy, it will be an invaluable reference work for researchers and students working on connectionist modelling in computer science and psychology, or in any area related to cognitive science.