7 papers
Solver-Guided Reasoning for Mixed-Equilibrium Strategies
Han Wang, Philippe Beardsell, Boning Li +4
Reasoning in large language models (LLMs) is often grounded in human text, human demonstrations, and human-generated rationales. For equilibrium reasoning in complex games, however…
Epistemic Gain, Aleatoric Cost: Uncertainty Decomposition in Multi-Agent Debate for Math Reasoning
Dan Qiao, Binbin Chen, Fengyu Cai +7
Multi-Agent Debate (MAD) has shown promise in improving reasoning and reducing hallucinations, yet it remains unclear how information exchange shapes individual reasoning behavior.…
PokerSkill: LLMs Can Play Expert-Level Poker without Training or Solvers
Boning Li, Baoxiang Wang, Longbo Huang
Poker is a landmark challenge for artificial intelligence. The dominant approach relies on equilibrium solvers built on counterfactual regret minimization, requiring millions of co…
Offline Multi-agent Reinforcement Learning via Sequential Score Decomposition
Dan Qiao, Wenhao Li, Shanchao Yang +2
Offline cooperative multi-agent reinforcement learning (MARL) faces unique challenges due to distributional shifts, particularly stemming from the high dimensionality of joint acti…
The Reciprocity Gradient
Yue Lin, Pascal Poupart, Shuhui Zhu +5
Communication is fundamental to sustaining reciprocity and cooperation in strategic interactions. We identify and formulate the influence attribution problem as the central optimiz…
Learning to Communicate Through Implicit Communication Channels
Han Wang, Binbin Chen, Tieying Zhang +1
Effective communication is an essential component in collaborative multi-agent systems. Situations where explicit messaging is not feasible have been common in human society throug…