We show that in perfect-information stochastic parity games with a finite state space both players have optimal pure positional strategies. Contrary to the recent proofs of this f...
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Abstract. In this work, we address the problem of transient and steadystate analysis of a stochastic Petri net which includes non Markovian distributions with a finite support but ...
It is unknown how to include stochastic process variation into fast-multipole-method (FMM) for a full chip capacitance extraction. This paper presents a parallel FMM extraction us...