**** Book Announcement ****
Integrating Rules and Conenctionism for Robust
Commonsense Reasoning
Author: Ron Sun
Publisher: John Wiley and Sons, Inc.
1-800-call-wiley
605 Third Ave.
New York, NY 10158-0012 USA
(212) 850-6589 FAX: (212) 850-6088
(ISBN 0-471-59324-9)
http://catalog.wiley.com/
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One of the outstanding problems
for artificial intelligence isthe problem of better modeling commonsense
reasoningand alleviating brittleness of traditional symbolic rule-based
models.This work tackles this problem by trying to combining rules withconnectionist
models in an integrated framework.This idea leads to the development of
a connectionistarchitecture with dual representation combining symbolic
and subsymbolic(feature-based) processing for evidential robust reasoning:
CONSYDERR.Reasoning data are analyzed based on the notions of
rules and similarity and modeled by the architecture which carries
outrule application and similarity matching through interaction of the
two levels;formal analyses are performed to understand rule encoding in
connectionistmodels, in order to prove that it handles a superset of Horn
clause logic anda nonmonotonic logic; the notion of causality is explored
for the purposeof clarifying how the proposed architecture can better capture
commonsensereasoning, and it is shown that causal knowledge can be well
represented by CONSYDERR and utilized in reasoning, which further
justifies the designof the architecture; the variable binding problem is
addressed, and a solutionis proposed within this architecture and is shown
to surpass existing ones;several aspects of the architecture are discussed
to demonstrate howconnectionist models can supplement, enhance, and integrate
symbolicrule-based reasoning; large-scale application-oriented systems
are prototyped.This architecture utilizes the synergy resulting from the
interaction ofthe two different types of representation and processing,
and is thereforecapable of handling a large number of difficult issues
in one integratedframework, such as partial and inexact information, cumulative
evidentialcombination, lack of exact match, similarity-based inference,
inheritance,and representational interactions, all of which are proven
to be crucialelements of commonsense reasoning. The results show that connectionismcoupled
with symbolic processing capabilities can be effective andefficient models
of reasoning for both theoretical and practical purposes.
Table of Content:
1 Introduction
1.1 Overview
1.2 Commonsense Reasoning
1.3 The Problem of Common Reasoning Patterns
1.4 What is the Point?
1.5 Some Clarifications
1.6 The Organization of the Book
1.7 Summary
2 Accounting for Commonsense Reasoning: A Framework with Rules and Similarities
2.1 Overview
2.2 Examples of Reasoning
2.3 Patterns of Reasoning
2.4 Brittleness of Rule-Based Reasoning
2.5 Towards a Solution
2.6 Some Reflections on Rules and Connectionism
2.7 Summary
3 A Connectionist Architecture for Commonsense Reasoning
3.1 Overview
3.2 A Generic Architecture
3.3 Fine-Tuning --- from Constraints to Specifications
3.4 Summary
3.5 Appendix
4 Evaluations and Experiments
4.1 Overview
4.2 Accounting for the Reasoning Examples
4.3 Evaluations of the Architecture
4.4 Systematic Experiments
4.5 Choice, Focus and Context
4.6 Reasoning with Geographical Knowledge
4.7 Applications to Other Domains
4.8 Summary
4.9 Appendix: Determining Similarities and CD representations
5 More on the Architecture: Logic and Causality
5.1 Overview
5.2 Causality in General
5.3 Shoham's Causal Theory
5.4 Defining FEL
5.5 Accounting for Commonsense Causal Reasoning
5.6 Determining Weights
5.7 Summary
5.8 Appendix: Proofs For Theorems
6 More on the Architecture: Beyond Logic
6.1 Overview
6.2 Further Analysis of Inheritance
6.3 Analysis of Interaction in Representation
6.4 Knowledge Acquisition, Learning, and Adaptation
6.5 Summary
7 An Extension: Variables and Bindings
7.1 Overview
7.2 The Variable Binding Problem
7.3 First-Order FEL
7.4 Representing Variables
7.5 A Formal Treatment
7.6 Dealing with Difficult Issues
7.7 Compilation
7.8 Correctness
7.9 Summary
7.10 Appendix
8 Reviews and Comparisons
8.1 Overview
8.2 Rule-Based Reasoning
8.3 Case-Based Reasoning
8.4 Connectionism
8.5 Summary
9 Conclusions
9.1 Overview
9.2 Some Accomplishments
9.3 Lessons Learned
9.4 Existing Limitations
9.5 Future Directions
9.6 Summary`
References
Go to
Prof. Ron Sun's Homepage