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Learning and Reasoning with Complex Representations [electronic resource] : PRICAI'96 Workshops on Reasoning with Incomplete and Changing Information and on Inducing Complex Representations Cairns, Australia, August 26-30, 1996, Selected Papers /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 1359Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1998Edition: 1st ed. 1998Description: XII, 288 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540697800
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
Inductive constraint logic programming: An overview -- Some approaches to reasoning with incomplete and changing information -- Curried least general generalization: A framework for higher order concept learning -- Approximate validity -- Inductive theories from equational systems -- The role of default representations in incremental learning -- Learning stable concepts in a changing world -- Inducing complex spatial descriptions in two dimensional scenes -- A framework for learning constraints: Preliminary report -- Induction of constraint logic programs -- Belief network algorithms: A study of performance based on domain characterisation -- A Group Decision and Negotiation Support System for argumentation based reasoning -- From belief revision to design revision: Applying theory change to changing requirements -- Using histories to model observations in theories of action -- Modelling inertia in action languages -- Combinatorial interpretation of uncertainty and conditioning -- Probabilistic diagnosis as an update problem -- Cooperative combination of default logic and autoepistemic logic.
In: Springer Nature eBookSummary: This book constitutes the thoroughly revised and refereed post-workshop documentation of two international workshops held in conjunction with the Pacific Rim International Conference on Artificial Intelligence, PRICAI'96, in Cairns, Australia, in August 1996. The volume presents 14 revised full papers togehter with two invited contributions and two introductory surveys particularly commissioned for this book. Among the topics addressed are computational learning, commonsense reasoning, constraint logic programming, fuzzy reasoning, vague data, inductive inference, belief revision, action theory, uncertainty, and probabilistic diagnosis.
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Inductive constraint logic programming: An overview -- Some approaches to reasoning with incomplete and changing information -- Curried least general generalization: A framework for higher order concept learning -- Approximate validity -- Inductive theories from equational systems -- The role of default representations in incremental learning -- Learning stable concepts in a changing world -- Inducing complex spatial descriptions in two dimensional scenes -- A framework for learning constraints: Preliminary report -- Induction of constraint logic programs -- Belief network algorithms: A study of performance based on domain characterisation -- A Group Decision and Negotiation Support System for argumentation based reasoning -- From belief revision to design revision: Applying theory change to changing requirements -- Using histories to model observations in theories of action -- Modelling inertia in action languages -- Combinatorial interpretation of uncertainty and conditioning -- Probabilistic diagnosis as an update problem -- Cooperative combination of default logic and autoepistemic logic.

This book constitutes the thoroughly revised and refereed post-workshop documentation of two international workshops held in conjunction with the Pacific Rim International Conference on Artificial Intelligence, PRICAI'96, in Cairns, Australia, in August 1996. The volume presents 14 revised full papers togehter with two invited contributions and two introductory surveys particularly commissioned for this book. Among the topics addressed are computational learning, commonsense reasoning, constraint logic programming, fuzzy reasoning, vague data, inductive inference, belief revision, action theory, uncertainty, and probabilistic diagnosis.

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