Social Laws for Multi-agent Coordination in Stochastic Environments

arXiv:2609.18929 · cs.MA, cs.AI, cs.LG · Submitted 2026-09-16 · Read on arXiv

cs.MA, cs.AI, cs.LG

Submitted: 2026-09-16

Updated: 2026-09-16

Comments: Appeared at the RIPL Workshop as part of ICAPS 2026

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

Terminology

• Robustness — 64× in this paper · explained in 5 episodes
• Verification — 15× in this paper · explained in 2 episodes
• Benchmark — 11× in this paper · explained in 2 episodes
• Multi-Agent System — 10× in this paper · explained in 6 episodes
• Action Space — 4× in this paper · explained in 1 episode
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Reward Function — 3× in this paper · explained in 2 episodes
• Cooperation — 2× in this paper · explained in 2 episodes
• Ad Hoc Teamwork — 1× in this paper · explained in 1 episode
• Adversarial Robustness — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fifteenth International Conference on Machine Learning — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Learning Agents Research Group — 1× in this paper
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

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