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.
Multi-Agent Pathfinding with Continuous Time
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abstract
Multi-Agent Pathfinding (MAPF) is the problem of finding paths for multiple agents such that every agent reaches its goal and the agents do not collide. Most prior work on MAPF was on grids, assumed agents' actions have uniform duration, and that time is discretized into timesteps. We propose a MAPF algorithm that does not rely on these assumptions, is complete, and provides provably optimal solutions. This algorithm is based on a novel adaptation of Safe interval path planning (SIPP), a continuous time single-agent planning algorithm, and a modified version of Conflict-based search (CBS), a state of the art multi-agent pathfinding algorithm. We analyze this algorithm, discuss its pros and cons, and evaluate it experimentally on several standard benchmarks.
fields
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.