This article presents a theoretical framework for probably approximately correct (PAC) multi-agent reinforcement learning (MARL) algorithms Markov games. Using the idea of delayed Q-learning, this extends well-known Nash Q-learning algorithm to build new PAC MARL general-sum In addition guiding design provably algorithm, enables checking whether an arbitrary is PAC. Comparative numerical result...

Probabilistic Computation Tree Logic (PCTL) is the established temporal logic for probabilistic verification of discrete-time Markov chains. Probabilistic model checking is a technique that verifies or refutes whether a property specified in this logic holds in a Markov chain. But Markov chains are often infinite or too large for this technique to apply. A standard solution to this problem is t...

A evolutionary game is introduced which explicitly models states and actions in the strategies of the organisms of the evolving population. The game principally features actions that result in demographic flow between states that may not conserve organism numbers. The game’s formalism is expounded and the nature of the game’s equilibrium is discussed. This discussion leads to an algorithm for n...