The design and control of autonomous systems that operate in uncertain or adversarial
environments can be facilitated by formal modeling and analysis. Probabilistic model …

We show that computing approximate stationary Markov coarse correlated equilibria (CCE)
in general-sum stochastic games is PPAD-hard, even when there are two players, the game …

Similar to the role of Markov decision processes in reinforcement learning, Markov games
(also called stochastic games) lay down the foundation for the study of multi-agent …

We summarize classical and recent results about two-player games played on graphs with ω-
regular objectives. These games have applications in the verification and synthesis of …

Synthesis is the automated construction of a system from its specification. The system has to
satisfy its specification in all possible environments. Modern systems often interact with other …

Due to the rapidly expanding complexity of the cyber-physical power systems, the probability
of a system malfunctioning and failing is increasing. Most of the existing works combining …

Synthesis is the automated construction of a system from its specification. The system has to
satisfy its specification in all possible environments. The environment often consists of …

Stochastic games provide a versatile model for reactive systems that are affected by random
events. This dissertation advances the algorithmic theory of stochastic games to incorporate …

We study pure-strategy Nash equilibria in multi-player concurrent deterministic games, for a
variety of preference relations. We provide a novel construction, called the suspect game …

Automated verification techniques for stochastic games allow formal reasoning about
systems that feature competitive or collaborative behaviour among rational agents in …