On characterization and existence of constrained correlated equilibria in Markov games
It addresses the theoretical gap of solution concepts for constrained multi-agent dynamical systems, which is crucial for applications like safety-critical environments.
This paper formalizes and characterizes constrained correlated equilibria in Markov games with coupling constraints, and provides a novel existence proof for such equilibria.
Markov games with coupling constraints model constrained dynamical decision-making involving self-interested agents, where the feasibility of an individual agent's strategy depends on the joint strategies of the others. Such games arise in numerous real-world applications involving safety requirements and budget caps, for example, in environmental management, electricity markets, and transportation systems. In unconstrained dynamical decision-making, the correlated equilibrium has emerged as a desired solution concept due to its computational tractability and amenability to learning algorithms. Understanding how coupling constraints shape correlated equilibria is a crucial step towards computing solutions in constrained Markov games. In this paper, we formalize and characterize the notion of constrained correlated equilibria for Markov games, defined as feasible joint policies where any unilateral deviation is either unprofitable or infeasible. Building on this characterization, we further study existence conditions for constrained correlated equilibria. In particular, we provide a novel existence proof of such equilibria in Markov games with coupling constraints.