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.

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