activity
20212024
most citedMARL-LNS: Cooperative Multi-agent Reinforcement Learning via Large Neighborhoods Search

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.MA2024

No Panacea in Planning: Algorithm Selection for Suboptimal Multi-Agent Path Finding

Weizhe Chen, Zhihan Wang, Jiaoyang Li +2

Since more and more algorithms are proposed for multi-agent path finding (MAPF) and each of them has its strengths, choosing the correct one for a specific scenario that fulfills s…

cs.MA20241 cited

MARL-LNS: Cooperative Multi-agent Reinforcement Learning via Large Neighborhoods Search

Weizhe Chen, Sven Koenig, Bistra Dilkina

Cooperative multi-agent reinforcement learning (MARL) has been an increasingly important research topic in the last half-decade because of its great potential for real-world applic…

cs.MA20241 cited

Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet

Weizhe Chen, Sven Koenig, Bistra Dilkina

With the explosive influence caused by the success of large language models (LLM) like ChatGPT and GPT-4, there has been an extensive amount of recent work showing that foundation…

cs.RO2023

Long-Term Autonomous Ocean Monitoring with Streaming Samples

Weizhe Chen, Lantao Liu

In the autonomous ocean monitoring task, the sampling robot moves in the environment and accumulates data continuously. The widely adopted spatial modeling method - standard Gaussi…

cs.RO2021

Multi-Objective Autonomous Exploration on Real-Time Continuous Occupancy Maps

Zheng Chen, Weizhe Chen, Shi Bai +1

Autonomous exploration in unknown environments using mobile robots is the pillar of many robotic applications. Existing exploration frameworks either select the nearest geometric f…