Structural Learning (Volume 2)

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Allen Newell
Arithmetic Language
associationist theory
Automata Theory
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Category=JMR
class
cognitive modelling
Complex Human Learning
computer simulation of cognition
Decoding Rules
Discourse Grammar
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equivalence
Equivalence Graph
Follow
Goal Situation
graph theory applications
Herbert A. Simon
higher
Higher Order Rules
Hold
Inference Rules
James G. Greeno
John Corcoran
Kenneth Lovell
Klaus G. Witz
Logical Consequence
mathematical competence research
Mathematical Systems
Mathematics Education
Merlin C. Wittrock
Michael A. Arbib
order
Patrick Suppes
Paul C. Rosenbloom
Piaget developmental models
Reinforcement Schedule
response
Robert E. Shaw
rule
Rule Set
rule-based learning
Sentential Grammars
stimulus
Stimulus Response Model
Stimulus Response Psychology
Stimulus Response Theorists
Stimulus Sampling Theory
Structural Learning
terminal
theory
Top Picture
vertex
Vice Versa
Zoltan Domotor

Product details

  • ISBN 9780415789172
  • Weight: 810g
  • Dimensions: 156 x 234mm
  • Publication Date: 18 Sep 2017
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Originally published in 1976, this title is an edited volume and reflects the major approaches being taken in structural learning at the time. Chapter 1 deals with the basic question of whether competence (knowledge) should be characterized in terms of rules (automata), on the one hand, or associations on the other. The bulk of Chapter 2 is devoted to a series of earlier experiments on rule learning by the editor and his associates. The two contributions in Chapter 3 deal with graph theoretical models. Piagetian models constitute the subject of Chapter 4. Chapter 5 deals with attempts to stimulate human behaviour with a computer. Chapter 6 ranges over a wide variety of competence models, with particular reference to logic and mathematics. In Chapter 7 the editor proposes a new theory of structural learning, together with some empirical results.