Multi-dimension Quantitative Games: Complexity and Strategy Synthesis

Quantitative verification and strategy synthesis for stochastic games

Design and control of computer systems that operate in uncertain, competitive or adversarial, environments can be facilitated by formal modelling and analysis. In this paper, we focus on analysis of complex computer systems modelled as turn-based 21/2-player games, or stochastic games for short, that are able to express both stochastic and non-stochastic uncertainty. We offer a systematic overv...

Strategy Complexity of Concurrent Safety Games

We consider two player, zero-sum, finite-state concurrent reachability games, played for an infinite number of rounds, where in every round, each player simultaneously and independently of the other players chooses an action, whereafter the successor state is determined by a probability distribution given by the current state and the chosen actions. Player 1 wins iff a designated goal state is ...

PRISM-Games 2.0: A Tool for Multi-objective Strategy Synthesis for Stochastic Games

We present a new release of PRISM-games, a tool for verification and strategy synthesis for stochastic games. PRISM-games 2.0 significantly extends its functionality by supporting, for the first time: (i) long-run average (mean-payoff) and ratio reward objectives, e.g., to express energy consumption per time unit; (ii) strategy synthesis and Pareto set computation for multi-objective properties...

The Complexity of Multi-Mean-Payoff and Multi-Energy Games

In mean-payoff games, the objective of the protagonist is to ensure that the limit average of an infinite sequence of numeric weights is nonnegative. In energy games, the objective is to ensure that the running sum of weights is always nonnegative. Multi-mean-payoff and multi-energy games replace individual weights by tuples, and the limit average (resp., running sum) of each coordinate must be...

Prototyping Pervasive Games: A New Dimension of Complexity