[2603.00808] MetaMind: General and Cognitive World Models in Multi-Agent Systems by Meta-Theory of Mind

Computer Science > Artificial Intelligence arXiv:2603.00808 (cs) [Submitted on 28 Feb 2026] Title:MetaMind: General and Cognitive World Models in Multi-Agent Systems by Meta-Theory of Mind Authors:Lingyi Wang, Rashed Shelim, Walid Saad, Naren Ramakrishna View a PDF of the paper titled MetaMind: General and Cognitive World Models in Multi-Agent Systems by Meta-Theory of Mind, by Lingyi Wang and 3 other authors View PDF HTML (experimental) Abstract:A major challenge for world models in multi-agent systems is to understand interdependent agent dynamics, predict interactive multi-agent trajectories, and plan over long horizons with collective awareness, without centralized supervision or explicit communication. In this paper, MetaMind, a general and cognitive world model for multi-agent systems that leverages a novel meta-theory of mind (Meta-ToM) framework, is proposed. Through MetaMind, each agent learns not only to predict and plan over its own beliefs, but also to inversely reason goals and beliefs from its own behavior trajectories. This self-reflective, bidirectional inference loop enables each agent to learn a metacognitive ability in a self-supervised manner. Then, MetaMind is shown to generalize the metacognitive ability from first-person to third-person through analogical reasoning. Thus, in multi-agent systems, each agent with MetaMind can actively reason about goals and beliefs of other agents from limited, observable behavior trajectories in a zero-shot manner, an...