Discusses the research steps needed to create a fully integrated DPLL(MAPF) solver for optimal multi-agent path finding via SMT, contrasting it with current loose integrations.
Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios
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abstract
Multi-agent path finding (MAPF) is well-studied in artificial intelligence, robotics, theoretical computer science and operations research. We discuss issues that arise when generalizing MAPF methods to real-world scenarios and four research directions that address them. We emphasize the importance of addressing these issues as opposed to developing faster methods for the standard formulation of the MAPF problem.
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cs.AI 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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On the Tour Towards DPLL(MAPF) and Beyond
Discusses the research steps needed to create a fully integrated DPLL(MAPF) solver for optimal multi-agent path finding via SMT, contrasting it with current loose integrations.