3 citations · 7 across the 7 of their papers we have counts for
7 papers
Dynamic Incentivized Cooperation under Changing Rewards
Philipp Altmann, Thomy Phan, Maximilian Zorn +2
Peer incentivization (PI) is a popular multi-agent reinforcement learning approach where all agents can reward or penalize each other to achieve cooperation in social dilemmas. Des…
Multi-Agent Path Finding Among Dynamic Uncontrollable Agents with Statistical Safety Guarantees
Kegan J. Strawn, Thomy Phan, Eric Wang +3
Existing multi-agent path finding (MAPF) solvers do not account for uncertain behavior of uncontrollable agents. We present a novel variant of Enhanced Conflict-Based Search (ECBS)…
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…
Confidence-Based Curriculum Learning for Multi-Agent Path Finding
Thomy Phan, Joseph Driscoll, Justin Romberg +1
A wide range of real-world applications can be formulated as Multi-Agent Path Finding (MAPF) problem, where the goal is to find collision-free paths for multiple agents with indivi…
Anytime Multi-Agent Path Finding using Operation Parallelism in Large Neighborhood Search
Shao-Hung Chan, Zhe Chen, Dian-Lun Lin +5
Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths for multiple agents in a shared environment while minimizing the sum of travel time. Since s…
Adaptive Anytime Multi-Agent Path Finding Using Bandit-Based Large Neighborhood Search
Thomy Phan, Taoan Huang, Bistra Dilkina +1
Anytime multi-agent path finding (MAPF) is a promising approach to scalable path optimization in large-scale multi-agent systems. State-of-the-art anytime MAPF is based on Large Ne…