Pattern-Directed Inference Systems

Pattern-Directed Inference Systems provides a description of the design and implementation of pattern-directed inference systems (PDIS) for various applications. The book also addresses the theoretical significance of PDIS for artificial intelligence and cognitive psychology.

The book is divided into eight sections. The introduction provides a brief overview of pattern-directed inference systems, including a historical perspective, a review of basic concepts, and a survey of work in this area. Subsequent chapters address topics on architecture and design, methods for accessing and controlling rule based systems, methods for obtaining adaptive behavior via rule-based systems and cognitive modeling. Constructing models of human information processing, natural language understanding and multilevel systems and complexity are described as well. The last section discusses the earlier chapters in the book and provides a unifying set of principles for the PDIS formalism.

Computer scientists, psychologists, engineers, and researchers in artificial intelligence will find the book very informative.

Contenu

List of Contributors
Preface
Introduction
An Overview of Pattern-Directed Inference Systems
Architecture and Design
Designing a Rule System That Searches for Scientific Discoveries
Use of Production Systems for Modeling Asynchronous, Concurrent Processes
Spontaneous Computation and Its Role in AI Modeling
Knowledge Acquisition in Rule-Based Systems-Knowledge About Representation as a Basis for System Construction and Maintenance
An Instructable Production System: Basic Design Issues
The Efficiency of Certain Production System Implementations
Production System Conflict Resolution Strategies
Deductive Inference
Semantic Network Representations in Rule-Based Inference Systems
Planning Techniques for Rule Selection in Deductive Question-Answering
Some Extensions of a System for Inference on Partial Information
Learning
Exemplary Programming in RITA
Inductive Learning of Relational Productions
Model-Directed Learning of Production Rules
Cognitive Systems Based on Adaptive Algorithms
Cognitive Modeling
Implications of Human Pattern Processing for the Design of Artificial Knowledge Systems
Pattern-Directed Processing of Knowledge from Texts
Knowledge-Directed Inference in BELIEVER
Natural Language Understanding
Conversational Action Patterns in Dialogs
An Expectation-Driven Production System for Natural Language Understanding
A Goal-Directed Production System for Story Understanding
Inferential Searches of Knowledge Networks as an Approach to Extensible Language-Understanding Systems
Rule-Based Computations on English
Multilevel Systems and Complexity
A Production System for Speech Understanding
Rule-Based Understanding of Signals
Pattern Recognition and Pattern-Directed Inference in a Program for Playing Go
The Production System: Architecture and Abstraction
Production Systems with Feedback
The Role of Partial and Best Matches in Knowledge Systems
Conclusion
Principles of Pattern-Directed Inference Systems
Bibliography
Author Index
Subject Index