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Markov Decision Processes with Multiple Long-run Average Objectives

Tomáš Brázdil ; Václav Brožek ; Krishnendu Chatterjee ; Vojtěch Forejt ; Antonín Kučera.

We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with k limit-average functions, in the expectation objective the goal is to maximize the expected&nbsp;[&hellip;]

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Algorithms for Game Metrics

Krishnendu Chatterjee ; Luca de Alfaro ; Rupak Majumdar ; Vishwanath Raman.

Simulation and bisimulation metrics for stochastic systems provide a quantitative generalization of the classical simulation and bisimulation relations. These metrics capture the similarity of states with respect to quantitative specifications written in the quantitative {\mu}-calculus and related&nbsp;[&hellip;]

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Expressiveness and Closure Properties for Quantitative Languages

Krishnendu Chatterjee ; Laurent Doyen ; Thomas A Henzinger.

Weighted automata are nondeterministic automata with numerical weights on transitions. They can define quantitative languages~$L$ that assign to each word~$w$ a real number~$L(w)$. In the case of infinite words, the value of a run is naturally computed as the maximum, limsup, liminf, limit-average,&nbsp;[&hellip;]

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Timed Parity Games: Complexity and Robustness

Krishnendu Chatterjee ; Thomas A. Henzinger ; Vinayak S. Prabhu.

We consider two-player games played in real time on game structures with clocks where the objectives of players are described using parity conditions. The games are \emph{concurrent} in that at each turn, both players independently propose a time delay and an action, and the action with the shorter&nbsp;[&hellip;]

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