The Cost of Classical Multi-Agent Path Finding

Key points

• Classical MAPF has been the dominant formulation for many years, with its assumptions of discrete time and graph-based conflicts presumably easing the search for solutions.1
• This work investigates how much solution quality, and in what contexts, the classical MAPF formulation forfeits.1
• Continuous-time MAPF (MAPF$R$) relaxes these assumptions, making it a natural counter-formulation to compare against across various agent counts and sizes, and graph connectedness, topologies, and resolutions.1
• We find that continuous time and agent shape consideration are worth relatively little on their own; their value comes from enabling an expanded range of move actions, on average improving solution quality by at least $5%$ on narrow and constrained maps and $17%$ on maps with open spaces.1

Sources (1)

• [1]The Cost of Classical Multi-Agent Path Finding
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 01:54 PM

  Multi-Agent Path Finding (MAPF) is the problem of planning conflict-free paths for multiple agents in a shared space, each from its start to its goal.

  Classical MAPF has been the dominant formulation for many years, with its assumptions of discrete time and graph-based conflicts presumably easing the search for solutions.

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