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Fast strong planning for fully observable nondeterministic planning problems

Annals of Mathematics and Artificial Intelligence(2016)

Cited 3|Views15
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Abstract
The ability to find strong solutions to fully observable nondeterministic (FOND) planning problems, if they exist, is desirable because unlike weak and strong-cyclic solutions, strong solutions are guaranteed to achieve the goal. However, only limited work has been done on FOND planning with strong solutions. In this paper, we present a sound and complete strong planning algorithm and incorporate it into our planner, FIP, which has achieved outstanding performance on strong cyclic planning problems. This new strong planning approach enables FIP to first search for strong solutions, and then search for strong-cyclic solutions only if strong solutions do not exist. We conduct extensive experiments to evaluate the new strong planning approach to (1) find a strong solution if one exists and (2) determine the non-existence of a strong solution. Experimental results demonstrate the superior performance of our planner to Gamer and MBP, the two best-known planners capable of solving strong FOND planning problems, on a variety of benchmark problems. Not only is our planner on average three orders of magnitude faster than Gamer and MBP, but it also scales up to larger problems.
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Key words
Fully observable nondeterministic planning (FOND),Strong-cyclic planning,Strong planning,Weak planning
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