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Heuristic search for planning with different forced goal-ordering constraints
Jiangfeng Luo1, Weiming Zhang, Jing Cui
1Science and Technology on Information Systems Engineering Laboratory, National University of Defense Technology, Changsha 410073, China.
Thescientificworldjournal
|August 13, 2013
Summary
Forced goal-ordering (FGO) constraints in AI planning arise from conflicting goal achievement operations. This study introduces a new multistep forward search algorithm to efficiently solve planning problems with these challenging FGOs.
Area of Science:
- Artificial Intelligence
- Automated Planning
Background:
- Forced goal-ordering (FGO) constraints are crucial in AI planning but pose significant challenges for plan generation.
- FGOs can be present initially or emerge during planning due to specific goal achievement operation (GAO) choices.
Purpose of the Study:
- To elucidate the origin of FGOs in planning problems, specifically identifying excludable constraints among GAOs as the root cause.
- To address the difficulties heuristic search planners face with FGOs.
Main Methods:
- Analysis of how excludable constraints among goal achievement operations (GAOs) introduce FGOs.
- Development and proposal of a novel multistep forward search algorithm.
Main Results:
- Demonstration that excludable constraints among GAOs are the source of FGOs in planning.
- The proposed algorithm effectively solves planning problems with various FGOs.
Conclusions:
- FGOs present a persistent challenge for heuristic search-based planners.
- The novel multistep forward search algorithm offers an efficient solution for planning problems with FGOs.
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