Integrating planning and acting in a case-based framework

Authors:
Kristian Hammond;Timothy Converse;Charles Martin
Affiliations:
The University of Chicago, Department of Computer Science, Artificial Intelligence Laboratory, Chicago, lL;The University of Chicago, Department of Computer Science, Artificial Intelligence Laboratory, Chicago, lL;The University of Chicago, Department of Computer Science, Artificial Intelligence Laboratory, Chicago, lL
Venue:
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 1
Year:
1990

Citing 6
Cited 2

Case-based planning: viewing planning as a memory task

Case-based planning: viewing planning as a memory task
Explaining and repairing plans that fail

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Direct memory access parsing

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Dynamic Memory: A Theory of Reminding and Learning in Computers and People

Dynamic Memory: A Theory of Reminding and Learning in Computers and People
Nonlinear planning: a rigorous reconstruction

IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 2
Opportunistic memory

IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1

The stabilization of environments

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Computational research on interaction and agency

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Abstract

This paper presents an outline of a theory of agency that seeks to integrate ongoing understanding, planning and activity into a single model of representation and processing. Our model of agency rises out of three basic pieces of work: Schank's structural model of memory organization (Schank, 1982), Hammond's work in case-based planning and dependency directed repair (Hammond, 1989d), and Martin's work in Direct Memory Access Parsing (Martin 1990). We see this paper as a first step in the production of a memory-based theory of agency: the active pursuit of goals in the face of a changing environment, that can exist within the computational constraints of a computer model.