MA-JEPA: Joint-Embedding World Models for Multi-Agent Reinforcement Learning

arXiv:2609.33563 · cs.LG, cs.AI, cs.MA · Submitted 2026-09-27 · Read on arXiv

cs.LG, cs.AI, cs.MA

Submitted: 2026-09-27

Updated: 2026-10-08

Code: https://github.com/DiXue98/DMAWM

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Actor — 43× in this paper · explained in 3 episodes
• World Model — 42× in this paper · explained in 7 episodes
• Transformer — 26× in this paper · explained in 2 episodes
• Reinforcement Learning — 23× in this paper · explained in 4 episodes
• Embeddings — 14× in this paper · explained in 2 episodes
• Benchmark — 8× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Adam — 7× in this paper · explained in 2 episodes
• Consistency — 7× in this paper · explained in 3 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Latent Dynamics — 4× in this paper · explained in 2 episodes
• Regularization — 4× in this paper · explained in 3 episodes
• StarCraft Multi-Agent Challenge — 4× in this paper
• Self-Supervised Learning — 3× in this paper · explained in 7 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Action-Conditioned Dynamics — 1× in this paper · explained in 1 episode
• Actor-Critic Learning — 1× in this paper · explained in 1 episode
• Agent Interactions — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Dec-POMDP — 1× in this paper · explained in 2 episodes
• Exponential Moving Average (EMA) — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Hypernetwork — 1× in this paper · explained in 2 episodes
• Multi-Agent Reinforcement Learning (MARL) — 1× in this paper · explained in 4 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Sample Efficiency — 1× in this paper · explained in 4 episodes

Sources

• When Does LeJEPA Learn a World Model?

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