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Found 5 papers, 2 papers with code
MARL-LNS: Cooperative Multi-agent Reinforcement Learning via Large Neighborhoods Search
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 applications.
Why Solving Multi-agent Path Finding with Large Language Model has not Succeeded Yet
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 models can be used to solve a large variety of tasks.
DiSProD: Differentiable Symbolic Propagation of Distributions for Planning
DiSProD builds a symbolic graph that captures the distribution of future trajectories, conditioned on a given policy, using independence assumptions and approximate propagation of distributions.
Temporal Induced Self-Play for Stochastic Bayesian Games
One practical requirement in solving dynamic games is to ensure that the players play well from any decision point onward.
Bi-level Actor-Critic for Multi-agent Coordination
Coordination is one of the essential problems in multi-agent systems.
Multiagent Systems
