1 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
Flaming-hot Initiation with Regular Execution Sampling for Large Language Models
Weizhe Chen, Zhicheng Zhang, Guanlin Liu +6
Since the release of ChatGPT, large language models (LLMs) have demonstrated remarkable capabilities across various domains. A key challenge in developing these general capabilitie…
RePrompt: Planning by Automatic Prompt Engineering for Large Language Models Agents
Weizhe Chen, Sven Koenig, Bistra Dilkina
In the past year, large language models (LLMs) have had remarkable success in domains outside the traditional natural language processing, and their capacity is further expanded in…
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…
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…
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…