MAPF-World, an autoregressive action world model that predicts future states and actions, is claimed to beat state-of-the-art learnable MAPF solvers while using 96.5% fewer parameters and 92% less data.
Neural discrete representation learning.Proceedings of the NeurIPS, 30, 2017
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MAPF-World: Action World Model for Multi-Agent Path Finding
MAPF-World, an autoregressive action world model that predicts future states and actions, is claimed to beat state-of-the-art learnable MAPF solvers while using 96.5% fewer parameters and 92% less data.