Real-time heuristic search: first results

Authors:
Richard E. Korf
Affiliations:
Computer Science Department, University of California, Los Angeles, Los Angeles, CA
Venue:
AAAI'87 Proceedings of the sixth National conference on Artificial intelligence - Volume 1
Year:
1987

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Abstract

Existing heuristic search algorithms are not applicable to real-time applications because they cannot commit to a move before an entire solution is found. We present a special case of minimax lookahead search to handle this problem, and an analog of alpha-beta pruning that significantly improves the efficiency of the algorithm. In addition, we present a new algorithm, called R.ea1-Time-A *, for searching when actions must actually be executed, as opposed to merely simulated. Finally, we examine the nature of the tradeoff between computation and execution cost.