Creating A Memory of Causal Relationships
An Integration of Empirical and Explanation-based Learning Methods
1st Edition
Published on 7. March 2013
360 pages
978-1-134-99225-6 (ISBN)
Description
This book presents a theory of learning new causal relationships by making use of perceived regularities in the environment, general knowledge of causality, and existing causal knowledge. Integrating ideas from the psychology of causation and machine learning, the author introduces a new learning procedure called theory-driven learning that uses abstract knowledge of causality to guide the induction process.
Known as OCCAM, the system uses theory-driven learning when new experiences conform to common patterns of causal relationships, empirical learning to learn from novel experiences, and explanation-based learning when there is sufficient existing knowledge to explain why a new outcome occurred. Together these learning methods construct a hierarchical organized memory of causal relationships. As such, OCCAM is the first learning system with the ability to acquire, via empirical learning, the background knowledge required for explanation-based learning.
Please note: This program runs on common lisp.
Known as OCCAM, the system uses theory-driven learning when new experiences conform to common patterns of causal relationships, empirical learning to learn from novel experiences, and explanation-based learning when there is sufficient existing knowledge to explain why a new outcome occurred. Together these learning methods construct a hierarchical organized memory of causal relationships. As such, OCCAM is the first learning system with the ability to acquire, via empirical learning, the background knowledge required for explanation-based learning.
Please note: This program runs on common lisp.
Reviews / Votes
"...the best source for learning about OCCAM...a clear and detailed description of OCCAM ....incorporates many interesting and novel ideas. The ideas that are emphasized by Pazzani, and that are explored in depth in the book, are a novel integration of explanation-based and similarity-based learning methods..."-Machine Learning
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
ISBN-13
978-1-134-99225-6 (9781134992256)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Michael J. Pazzani
Creating A Memory of Causal Relationships
An Integration of Empirical and Explanation-based Learning Methods
Book
04/1990
1st Edition
Psychology Press
€90.55
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Content
Contents: Introduction. What OCCAM Is Up Against. Similarity-Based Learning in OCCAM. Theory-Driven Learning in OCCAM. Explanation-Based Learning in OCCAM. Integration of Learning Methods. Experiments in Integrated Learning. Future Directions and Conclusions. Appendices: Data Listing. Program Traces. Prolog OCCAM. OCCAM's Generalization Rules. Listing of Economic Sanction Incidents.
