LOD: Latent Objective Discovery in Heterogeneous Multi-Agent Reinforcement Learning

arXiv:2505.09756 · cs.LG, cs.MA, math.OC, stat.ML · Submitted 2025-05-14 · Read on arXiv

cs.LG, cs.MA, math.OC, stat.ML

Submitted: 2025-05-14

Updated: 2026-09-26

Terminology

• Actor — 31× in this paper · explained in 3 episodes
• Reinforcement Learning — 17× in this paper · explained in 4 episodes
• Active Learning — 12× in this paper · explained in 6 episodes
• Transfer Learning — 9× in this paper · explained in 10 episodes
• Action Space — 4× in this paper · explained in 1 episode
• Active Exploration — 4× in this paper · explained in 2 episodes
• Multi-Agent System — 4× in this paper · explained in 6 episodes
• Reward Function — 4× in this paper · explained in 2 episodes
• Convergence Guarantees — 3× in this paper · explained in 3 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Multi-Agent Reinforcement Learning (MARL) — 3× in this paper · explained in 4 episodes
• Transferability — 3× in this paper · explained in 4 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Adjacency Matrix — 2× in this paper · explained in 1 episode
• Cooperation — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Causal Inference — 1× in this paper · explained in 4 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Community-based Multi-agent Markov Decision Process — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Decentralized Learning — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Information Gain — 1× in this paper · explained in 2 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes

Sources

• Multi-agent Reinforcement Learning for Networked System Control
• Off-Policy Actor-Critic
• Actor-Critic Algorithms for Learning Nash Equilibria in N-player General-Sum Games

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