The classical problem of reachability in simple stochastic games is typically solved by value
iteration (VI), which produces a sequence of under-approxima-tions of the value of the …

While value iteration (VI) is a standard solution approach to simple stochastic games
(SSGs), it suffered from the lack of a stopping criterion. Recently, several solutions have …

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 …

Simple stochastic games are turn-based 2½-player zero-sum graph games with a
reachability objective. The problem is to compute the winning probabilities as well as the …

Turn-based stochastic games (aka simple stochastic games) are two-player zero-sum
games played on directed graphs with probabilistic transitions. The goal of player-max is to …

Simple stochastic games are turn-based 2½-player games with a reachability objective. The
basic question asks whether one player can ensure reaching a given target with at least a …

This paper investigates the use of model-free reinforcement learning to compute the optimal
value in two-player stochastic games with parity objectives. In this setting, two decision …

We present a generic strategy iteration algorithm (GSIA) to find an optimal strategy of a
simple stochastic game (SSG). We prove the correctness of GSIA, and derive a general …

Game-theoretic techniques and equilibria analysis facilitate the design and verification of
competitive systems. While algorithmic complexity of equilibria computation has been …

We consider algorithms for parity games that use attractor decomposition, such as Zielonka's
recursive algorithm, priority promotion, and tangle learning. In earlier work, we identified the …