Symbolic controller synthesis for Büchi specifications on stochastic systems
We consider the policy synthesis problem for continuous-state controlled Markov processes
evolving in discrete time, when the specification is given as a Büchi condition (visit a set of …
evolving in discrete time, when the specification is given as a Büchi condition (visit a set of …
Strategy Complexity of B\" uchi Objectives in Concurrent Stochastic Games
S Kiefer, R Mayr, M Shirmohammadi… - arXiv preprint arXiv …, 2024 - arxiv.org
We study 2-player concurrent stochastic B\" uchi games on countable graphs. Two players,
Max and Min, seek respectively to maximize and minimize the probability of visiting a set of …
Max and Min, seek respectively to maximize and minimize the probability of visiting a set of …
Strategy complexity of parity objectives in countable mdps
S Kiefer, R Mayr, M Shirmohammadi… - arXiv preprint arXiv …, 2020 - arxiv.org
We study countably infinite MDPs with parity objectives. Unlike in finite MDPs, optimal
strategies need not exist, and may require infinite memory if they do. We provide a complete …
strategies need not exist, and may require infinite memory if they do. We provide a complete …
Strategy complexity of reachability in countable stochastic 2-player games
S Kiefer, R Mayr, M Shirmohammadi… - Dynamic Games and …, 2024 - Springer
We study countably infinite stochastic 2-player games with reachability objectives. Our
results provide a complete picture of the memory requirements of ε-optimal (resp. optimal) …
results provide a complete picture of the memory requirements of ε-optimal (resp. optimal) …
Transience in countable MDPs
S Kiefer, R Mayr, M Shirmohammadi… - arXiv preprint arXiv …, 2020 - arxiv.org
The Transience objective is not to visit any state infinitely often. While this is not possible in
finite Markov Decision Process (MDP), it can be satisfied in countably infinite ones, eg, if the …
finite Markov Decision Process (MDP), it can be satisfied in countably infinite ones, eg, if the …
Strategy Complexity of Mean Payoff, Total Payoff and Point Payoff Objectives in Countable MDPs
R Mayr, E Munday - arXiv preprint arXiv:2107.03287, 2021 - arxiv.org
We study countably infinite Markov decision processes (MDPs) with real-valued transition
rewards. Every infinite run induces the following sequences of payoffs: 1. Point payoff (the …
rewards. Every infinite run induces the following sequences of payoffs: 1. Point payoff (the …
How to play in infinite MDPs (invited talk)
S Kiefer, R Mayr, M Shirmohammadi… - 47th International …, 2020 - research.ed.ac.uk
Markov decision processes (MDPs) are a standard model for dynamic systems that exhibit
both stochastic and nondeterministic behavior. For MDPs with finite state space it is known …
both stochastic and nondeterministic behavior. For MDPs with finite state space it is known …
Strategy complexity of point payoff, mean payoff and total payoff objectives in countable MDPs
R Mayr, E Munday - Logical Methods in Computer Science, 2023 - lmcs.episciences.org
We study countably infinite Markov decision processes (MDPs) with real-valued transition
rewards. Every infinite run induces the following sequences of payoffs: 1. Point payoff (the …
rewards. Every infinite run induces the following sequences of payoffs: 1. Point payoff (the …
Superfair Stochastic Games
A two-person zero-sum stochastic game with a nonnegative stage reward function is
superfair if the value of the one-shot game at each state is at least as large as the reward …
superfair if the value of the one-shot game at each state is at least as large as the reward …
Approximations of expectations under infinite product measures
We are given a bounded Borel-measurable real-valued function on a product of countably
many Polish spaces, and a product probability measure. We are interested in points in the …
many Polish spaces, and a product probability measure. We are interested in points in the …