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Unifying Two Views on Multiple Mean-Payoff Objectives in Markov Decision Processes

Krishnendu Chatterjee ; Zuzana Křetínská ; Jan Křetínský.

We consider Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) objectives. There exist two different views: (i) the expectation semantics, where the goal is to optimize the expected mean-payoff objective, and (ii) the satisfaction semantics, where the goal is to maximize&nbsp;[&hellip;]

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Edit Distance for Pushdown Automata

Krishnendu Chatterjee ; Thomas A. Henzinger ; Rasmus Ibsen-Jensen ; Jan Otop.

The edit distance between two words $w_1, w_2$ is the minimal number of word operations (letter insertions, deletions, and substitutions) necessary to transform $w_1$ to $w_2$. The edit distance generalizes to languages $\mathcal{L}_1, \mathcal{L}_2$, where the edit distance from $\mathcal{L}_1$ to&nbsp;[&hellip;]

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Improved Algorithms for Parity and Streett objectives

Krishnendu Chatterjee ; Monika Henzinger ; Veronika Loitzenbauer.

The computation of the winning set for parity objectives and for Streett objectives in graphs as well as in game graphs are central problems in computer-aided verification, with application to the verification of closed systems with strong fairness conditions, the verification of open systems,&nbsp;[&hellip;]

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