概要
Markov Game ACSet is a specialized skill designed to bridge the gap between compositional open games and state-dependent stochastic processes. By leveraging the AlgebraicJulia ACSet framework, it enables developers and researchers to model complex multi-agent interactions where strategy spaces and payoffs depend on the current environment state. The skill introduces rigorous constraints such as derangement-constrained transitions—ensuring information reflow by preventing self-loops—and GF(3) trit conservation across state changes. It is an essential tool for formalizing economic protocols, decentralized systems, and game-theoretic models that require rigorous categorical foundations.
