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Trace Refinement in Labelled Markov Decision Processes

Nathanaël Fijalkow ; Stefan Kiefer ; Mahsa Shirmohammadi.

Given two labelled Markov decision processes (MDPs), the trace-refinement problem asks whether for all strategies of the first MDP there exists a strategy of the second MDP such that the induced labelled Markov chains are trace-equivalent. We show that this problem is decidable in polynomial time if&nbsp;[&hellip;]

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The Theory of Universal Graphs for Infinite Duration Games

Thomas Colcombet ; Nathanaël Fijalkow ; Paweł Gawrychowski ; Pierre Ohlmann.

We introduce the notion of universal graphs as a tool for constructing algorithms solving games of infinite duration such as parity games and mean payoff games. In the first part we develop the theory of universal graphs, with two goals: showing an equivalence and normalisation result between&nbsp;[&hellip;]

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Playing Safe, Ten Years Later

Thomas Colcombet ; Nathanaël Fijalkow ; Florian Horn.

We consider two-player games over graphs and give tight bounds on the memory size of strategies ensuring safety objectives. More specifically, we show that the minimal number of memory states of a strategy ensuring a safety objective is given by the size of the maximal antichain of left quotients&nbsp;[&hellip;]

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