Stochastic Games

Value Iteration for Simple Stochastic Games: Stopping Criterion and Learning Algorithm

Simple stochastic games can be solved by value iteration (VI), which yields a sequence of under-approximations of the value of the game. This sequence is guaranteed to converge to the value only in the limit. Since no stopping criterion is known, …

Deciding Maxmin Reachability in Half-Blind Stochastic Games

Two-player, turn-based, stochastic games with reachability conditions are considered, where the maximizer has no information (he is blind) and is restricted to deterministic strategies whereas the minimizer is perfectly informed. We ask the question …

Two-Player Perfect-Information Shift-Invariant Submixing Stochastic Games are Half-Positional

We consider zero-sum stochastic games with perfect information and finitely many states and actions. The payoff is computed by a function which associates to each infinite sequence of states and actions a real number. We prove that if the the payoff …