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New framework for social laws in stochastic multi-agent systems unveiled

This paper introduces a new framework for social laws in multi-agent systems operating in stochastic environments. It extends previous work from deterministic settings to reward-based scenarios, proposing a method for defining and verifying the robustness of these laws. The research introduces a concept called \"alpha-robustness\" to quantify the guaranteed utility for agents adhering to the social law while pursuing their optimal policies. The authors present a verification approach that reduces the problem to solving multiple Markov decision processes and demonstrate its potential through empirical evaluations. AI

IMPACT This research could lead to more robust and efficient coordination in complex AI systems with multiple interacting agents.

RANK_REASON The cluster contains an academic paper published on arXiv detailing a new theoretical framework and verification method for multi-agent systems.

Read on arXiv cs.MA (Multiagent) →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New framework for social laws in stochastic multi-agent systems unveiled

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The cluster contains an academic paper published on arXiv detailing a new theoretical framework and verification method for multi-agent systems.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Rolando Fernandez, Caleb Probine, Tyler Lee, Jeffrey Chen, Erez Karpas, Muhammad Arrasy Rahman, Peter Stone, Ufuk Topcu ·

    Social Laws for Multi-agent Coordination in Stochastic Environments

    arXiv:2609.18929v1 Announce Type: cross Abstract: In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous research on social laws for multi-agent systems has primarily focused on determini…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Ufuk Topcu ·

    Social Laws for Multi-agent Coordination in Stochastic Environments

    In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous research on social laws for multi-agent systems has primarily focused on deterministic, goal-based settings. This paper extends the …