Stabilizing environments to facilitate planning and activity: an engineering argument

Authors:
Kristian J. Hammond;Timothy M. Converse
Affiliations:
Department of Computer Science, The University of Chicago, Chicago, IL;Department of Computer Science, The University of Chicago, Chicago, IL
Venue:
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Year:
1991

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Abstract

An underlying assumption of research on learning from planning and activity is that agents can exploit regularities they find in the world. For agents that interact with a world over an extended period of time, there is another possibility: the exploited regularities can be created and maintained, rather than discovered. We explore the ways in which agents can actively stabilize the world to increase the predictability and tractability of acting within in it.