Soar User's Manual
                                  Version 6
                                  Edition 1
                                      
                    John E. Laird and Clare Bates Congdon
                                      
           Electrical Engineering and Computer Science Department
                           University of Michigan
                                      
                      Erik Altmann and Robert Doorenbos
                         School of Computer Science
                         Carnegie Mellon University
                                      
                                October 1993

Copyright (C) 1993, J. E. Laird, C. B. Congdon, E. Altmann, and B. Doorenbos.

This research was sponsored in part by NASA Ames under grant NCC2-517; in
part by the Advanced Research Projects Agency (DOD) and monitored by the
Naval Research Laboratory under contract N00014-92-K-2015.  The views and
conclusions contained in this document are those of the authors and should
not be interpreted as representing the official policies, either expressed or
implied, of NASA, the Advanced Research Projects Agency, or the U.S.
Government.

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Preface

About Soar, this manual, SDE, & mailing lists

Introduction

Introduction to Soar.

The Problem Space Level

Soar's Problem Space Computational Model.

Semantics of the Symbol Level

Soar's Symbol Level Semantics.

Syntax of the Symbol Level

Soar's Symbol Level Syntax.

Learning in Soar

Chunking, Soar's learning mechanism.

I/O

Input/output in Soar programs.

Default Knowledge in Soar

Soar's default knowledge.

Encoding A Task in Soar

Example task implementation.

User Interface

Soar's user interface.

Support of Preferences

Soar's persistence scheme.

Multiple Agents

The multiple agent capabilities of Soar.

Glossary of Terms

Soar terminology.

Summary of Functions

User-level functions in Soar.

Index

Index to functions, terms, concepts, etc.

This manual is available in printed form from The Soar Group, School of

Computer Science, Carnegie Mellon University, and from the AI Laboratory, The

University of Michigan. For information, please send Internet electronic

mail to `soar-requests@cs.cmu.edu', or regular mail to The Soar Group.