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no code implementations • 5 May 2021 • František Blahoudek, Petr Novotný, Melkior Ornik, Pranay Thangeda, Ufuk Topcu

We consider qualitative strategy synthesis for the formalism called consumption Markov decision processes.

no code implementations • 13 Jul 2018 • Nikhil Balaji, Stefan Kiefer, Petr Novotný, Guillermo A. Pérez, Mahsa Shirmohammadi

We show that, given a horizon $n$ in binary and an MDP, computing an optimal policy is EXP-complete, thus resolving an open problem that goes back to the seminal 1987 paper on the complexity of MDPs by Papadimitriou and Tsitsiklis.

no code implementations • 27 Apr 2018 • Krishnendu Chatterjee, Adrián Elgyütt, Petr Novotný, Owen Rouillé

We consider the expectation optimization with probabilistic guarantee (EOPG) problem, where the goal is to optimize the expectation ensuring that the payoff is above a given threshold with at least a specified probability.

1 code implementation • 26 Nov 2016 • Krishnendu Chatterjee, Petr Novotný, Guillermo A. Pérez, Jean-François Raskin, Đorđe Žikelić

In this work we go beyond both the "expectation" and "threshold" approaches and consider a "guaranteed payoff optimization (GPO)" problem for POMDPs, where we are given a threshold $t$ and the objective is to find a policy $\sigma$ such that a) each possible outcome of $\sigma$ yields a discounted-sum payoff of at least $t$, and b) the expected discounted-sum payoff of $\sigma$ is optimal (or near-optimal) among all policies satisfying a).

no code implementations • 24 Feb 2016 • Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelík, Anchit Gupta, Petr Novotný

Finally, we show experimentally that our algorithm performs well and computes succinct policies on a number of POMDP instances from the literature that were naturally enhanced with energy levels.

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