Ebook: Learning and Reasoning with Complex Representations: PRICAI'96 Workshops on Reasoning with Incomplete and Changing Information and on Inducing Complex Representations Cairns, Australia, August 26–30, 1996 Selected Papers

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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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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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.
Content:
Front Matter....Pages -
Inductive constraint logic programming: An overview....Pages 1-8
Some approaches to reasoning with incomplete and changing information....Pages 9-44
Curried least general generalization: A framework for higher order concept learning....Pages 45-60
Approximate validity....Pages 61-77
Inductive theories from equational systems....Pages 78-91
The role of default representations in incremental learning....Pages 92-105
Learning stable concepts in a changing world....Pages 106-122
Inducing complex spatial descriptions in two dimensional scenes....Pages 123-132
A framework for learning constraints: Preliminary report....Pages 133-147
Induction of constraint logic programs....Pages 148-167
Belief network algorithms: A study of performance based on domain characterisation....Pages 168-187
A Group Decision and Negotiation Support System for argumentation based reasoning....Pages 188-205
From belief revision to design revision: Applying theory change to changing requirements....Pages 206-220
Using histories to model observations in theories of action....Pages 221-233
Modelling inertia in action languages....Pages 234-247
Combinatorial interpretation of uncertainty and conditioning....Pages 248-255
Probabilistic diagnosis as an update problem....Pages 256-266
Cooperative combination of default logic and autoepistemic logic....Pages 267-283
Back Matter....Pages -

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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.
Content:
Front Matter....Pages -
Inductive constraint logic programming: An overview....Pages 1-8
Some approaches to reasoning with incomplete and changing information....Pages 9-44
Curried least general generalization: A framework for higher order concept learning....Pages 45-60
Approximate validity....Pages 61-77
Inductive theories from equational systems....Pages 78-91
The role of default representations in incremental learning....Pages 92-105
Learning stable concepts in a changing world....Pages 106-122
Inducing complex spatial descriptions in two dimensional scenes....Pages 123-132
A framework for learning constraints: Preliminary report....Pages 133-147
Induction of constraint logic programs....Pages 148-167
Belief network algorithms: A study of performance based on domain characterisation....Pages 168-187
A Group Decision and Negotiation Support System for argumentation based reasoning....Pages 188-205
From belief revision to design revision: Applying theory change to changing requirements....Pages 206-220
Using histories to model observations in theories of action....Pages 221-233
Modelling inertia in action languages....Pages 234-247
Combinatorial interpretation of uncertainty and conditioning....Pages 248-255
Probabilistic diagnosis as an update problem....Pages 256-266
Cooperative combination of default logic and autoepistemic logic....Pages 267-283
Back Matter....Pages -
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