6 citations · 9 across the 7 of their papers we have counts for
4 papers · 1 filter
Belief-Aware Multi-Agent Path Finding under Map Uncertainty
Viraj Parimi, Shao-Hung Chan, Han Zhang +2
Multi-Agent Path Finding (MAPF) aims to find collision-free paths for multiple agents in a shared environment. Classical MAPF assumes that all static obstacles are known in advance…
New Mechanisms in Flex Distribution for Bounded Suboptimal Multi-Agent Path Finding
Shao-Hung Chan, Thomy Phan, Jiaoyang Li +1
Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths, one for each agent in a shared environment. Its objective is to minimize the sum of path co…
Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic
Thomy Phan, Benran Zhang, Shao-Hung Chan +1
Anytime multi-agent path finding (MAPF) is a promising approach to scalable path optimization in multi-agent systems. MAPF-LNS, based on Large Neighborhood Search (LNS), is the cur…
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World
Florian Laurent, Manuel Schneider, Christian Scheller +24
The Flatland competition aimed at finding novel approaches to solve the vehicle re-scheduling problem (VRSP). The VRSP is concerned with scheduling trips in traffic networks and th…