AAAI Publications, Sixth Annual Symposium on Combinatorial Search

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Experimental Real-Time Heuristic Search Results in a Video Game
Ethan Burns, Scott Kiesel, Wheeler Ruml

Last modified: 2013-06-19

Abstract


In real-time domains such as video games, a planning algo- rithm has a strictly bounded time before it must return the next action for the agent to execute. We introduce a realistic video game benchmark domain that is useful for evaluating real-time heuristic search algorithms. Unlike previous bench- marks such as grid pathfinding and the sliding tile puzzle, this new domain includes dynamics and induces a directed graph. Using both the previous and new domains, we investigate sev- eral enhancements to a leading real-time search algorithm, LSS-LRTA*. We show experimentally that 1) it is not dif- ficult to outperform A* when optimizing goal achievement time, 2) it is better to plan after each action than to commit to multiple actions or to use a dynamically sized lookahead, 3) A*-based lookahead can cause undesirable actions to be selected, and 4) on-line de-biasing of the heuristic can lead to improved performance. We hope that this new domain and results will stimulate further research on applying real-time search to dynamic real-time domains.

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