Introduction

  • Steven E. Hampson

Abstract

The model developed here, which is actually more a collection of components than a single monolithic structure, traces a path from relatively low-level neural/connectionistic structures and processes to relatively high-level animal/artificial intelligence behaviors. Incremental extension of this initial path permits increasingly sophisticated representation and processing strategies, and consequently increasingly sophisticated behavior. The initial chapters develop the basic components of the system at the node and network level, with the general goal of efficient category learning and representation. The later chapters are more concerned with the problems of assembling sequences of actions in order to achieve a given goal state.

Keywords

Goal State Intelligent Behavior Connectionistic Problem Adaptive Problem Connectionist Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Birkhäuser Boston 1990

Authors and Affiliations

  • Steven E. Hampson
    • 1
  1. 1.Department of Information & Computer ScienceUniversity of CaliforniaIrvineUSA

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