activity
20172019
most citedOverview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios

91 citations · 253 across the 7 of their papers we have counts for

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11 papers · 1 filter

cs.AI2019

Idle Time Optimization for Target Assignment and Path Finding in Sortation Centers

Ngai Meng Kou, Cheng Peng, Hang Ma +2

In this paper, we study the one-shot and lifelong versions of the Target Assignment and Path Finding problem in automated sortation centers, where each agent needs to constantly as…

cs.AI2019

Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks

Roni Stern, Nathan Sturtevant, Ariel Felner +9

The MAPF problem is the fundamental problem of planning paths for multiple agents, where the key constraint is that the agents will be able to follow these paths concurrently witho…

cs.AI20182 cited

Searching with Consistent Prioritization for Multi-Agent Path Finding

Hang Ma, Daniel Harabor, Peter J. Stuckey +2

We study prioritized planning for Multi-Agent Path Finding (MAPF). Existing prioritized MAPF algorithms depend on rule-of-thumb heuristics and random assignment to determine a fixe…

cs.AI201818 cited

Lifelong Path Planning with Kinematic Constraints for Multi-Agent Pickup and Delivery

Hang Ma, Wolfgang Hönig, T. K. Satish Kumar +2

The Multi-Agent Pickup and Delivery (MAPD) problem models applications where a large number of agents attend to a stream of incoming pickup-and-delivery tasks. Token Passing (TP) i…

cs.AI2018

Multi-Agent Path Finding with Deadlines

Hang Ma, Glenn Wagner, Ariel Felner +3

We formalize Multi-Agent Path Finding with Deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their given start ve…

cs.AI2018

Multi-Agent Path Finding with Deadlines: Preliminary Results

Hang Ma, Glenn Wagner, Ariel Felner +3

We formalize the problem of multi-agent path finding with deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their…