A feed-forward neural network using Action Dependency Graph features estimates the benefit of replanning in delayed MAPF executions and reduces delay impact by up to 94.6% of the achievable amount.
RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks (Extended Abstract)
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Should I Replan? Learning to Spot the Right Time in Robust MAPF Execution
A feed-forward neural network using Action Dependency Graph features estimates the benefit of replanning in delayed MAPF executions and reduces delay impact by up to 94.6% of the achievable amount.