Body-Reservoir Governance in Repeated Games: Embodied Decision-Making, Dynamic Sentinel Adaptation, and Complexity-Regularized Optimization
Yuki Nakamura

TL;DR
This paper introduces a three-layer Body-Reservoir Governance architecture that enables embodied agents to achieve cooperation through implicit inference and adaptive decision-making, reducing computational costs and enhancing resilience in repeated games.
Contribution
It presents a novel three-layer framework combining reservoir computing, strategic filtering, and metacognitive regulation for embodied cooperation, emphasizing implicit inference over explicit computation.
Findings
Reservoir-based body governance significantly reduces strategy complexity costs.
Dynamic sentinel-driven adaptation improves cooperation and payoff outcomes.
Implicit inference scales with bodily richness, enhancing cooperative robustness.
Abstract
Standard game theory explains cooperation in repeated games through conditional strategies such as Tit-for-Tat (TfT), but these require continuous computation that imposes physical costs on embodied agents. We propose a three-layer Body-Reservoir Governance (BRG) architecture: (1) a body reservoir (echo state network) whose -dimensional state performs implicit inference over interaction history, serving as both decision-maker and anomaly detector, (2) a cognitive filter providing costly strategic tools activated on demand, and (3) a metacognitive governance layer with receptivity parameter . At full body governance (), closed-loop dynamics satisfy a self-consistency equation: cooperation is expressed as the reservoir's fixed point, not computed. Strategy complexity cost is defined as the KL divergence between the reservoir's state distribution and its…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNeural Networks and Reservoir Computing · Model Reduction and Neural Networks · Embodied and Extended Cognition
