26 citations · 55 across the 9 of their papers we have counts for
10 papers · 1 filter
Cost Splitting for Multi-Objective Conflict-Based Search
Cheng Ge, Han Zhang, Jiaoyang Li +1
The Multi-Objective Multi-Agent Path Finding (MO-MAPF) problem is the problem of finding the Pareto-optimal frontier of collision-free paths for a team of agents while minimizing m…
Pairwise Symmetry Reasoning for Multi-Agent Path Finding Search
Jiaoyang Li, Daniel Harabor, Peter J. Stuckey +1
Multi-Agent Path Finding (MAPF) is a challenging combinatorial problem that asks us to plan collision-free paths for a team of cooperative agents. In this work, we show that one of…
Learning to Resolve Conflicts for Multi-Agent Path Finding with Conflict-Based Search
Taoan Huang, Bistra Dilkina, Sven Koenig
Conflict-Based Search (CBS) is a state-of-the-art algorithm for multi-agent path finding. At the high level, CBS repeatedly detects conflicts and resolves one of them by splitting…
EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding
Jiaoyang Li, Wheeler Ruml, Sven Koenig
Multi-Agent Path Finding (MAPF), i.e., finding collision-free paths for multiple robots, is important for many applications where small runtimes are necessary, including the kind o…
Integer Programming for Multi-Robot Planning: A Column Generation Approach
Naveed Haghani, Jiaoyang Li, Sven Koenig +3
We consider the problem of coordinating a fleet of robots in a warehouse so as to maximize the reward achieved within a time limit while respecting problem and robot specific const…
Lifelong Multi-Agent Path Finding in Large-Scale Warehouses
Jiaoyang Li, Andrew Tinka, Scott Kiesel +3
Multi-Agent Path Finding (MAPF) is the problem of moving a team of agents to their goal locations without collisions. In this paper, we study the lifelong variant of MAPF, where ag…