Can asymmetric agents ever share knowledge?
Unattainability of Common Knowledge in Asymmetric Games with Imperfect Information
This paper explores the difficulty of achieving common knowledge in asymmetric multi-agent systems where agents have different capabilities and limited information. It presents a simple game with two agents (a human and an AI) interacting with an alarm clock where the human can act but has incomplete information about the alarm's state, while the AI has perfect information but cannot act. Using epistemic logic, the paper proves that even with repeated interactions, common knowledge about the alarm's state is unattainable.
For LLM-based multi-agent systems, this highlights the significant challenges of coordinating actions and achieving shared understanding when agents have different information access and capabilities, even in seemingly simple scenarios. The paper suggests that limitations in information flow due to asymmetry can prevent agents from converging on a shared understanding of the world, which is crucial for effective cooperation. This is especially relevant for LLM-based agents with diverse roles and access levels within a larger application.