activity
20052023
most citedDecisive Markov Chains

52 citations · 206 across the 25 of their papers we have counts for

collaborators

30 papers

cs.GT2023

Approximating the Value of Energy-Parity Objectives in Simple Stochastic Games

Mohan Dantam, Richard Mayr

We consider simple stochastic games with energy-parity objectives, a combination of quantitative rewards with a qualitative parity condition. The Maximizer tries to av…

math.OC2022

Strategy Complexity of Limsup and Liminf Threshold Objectives in Countable MDPs, with Applications to Optimal Expected Payoffs

Richard Mayr, Eric Munday

We study Markov decision processes (MDPs) with a countably infinite number of states. The (resp. ) threshold objective is to maximize the probability that the $\…

cs.GT2022

Strategy Complexity of Reachability in Countable Stochastic 2-Player Games

Stefan Kiefer, Richard Mayr, Mahsa Shirmohammadi +1

We study countably infinite stochastic 2-player games with reachability objectives. Our results provide a complete picture of the memory requirements of -optimal (resp…

cs.CC2022★ 1 cited

Strategy Complexity of Point Payoff, Mean Payoff and Total Payoff Objectives in Countable MDPs

Richard Mayr, Eric Munday

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 (th…

cs.AI2021

Strategy Complexity of Mean Payoff, Total Payoff and Point Payoff Objectives in Countable MDPs

Richard Mayr, Eric Munday

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 (th…

cs.GT2021

Simple Stochastic Games with Almost-Sure Energy-Parity Objectives are in NP and coNP

Richard Mayr, Sven Schewe, Patrick Totzke +1

We study stochastic games with energy-parity objectives, which combine quantitative rewards with a qualitative -regular condition: The maximizer aims to avoid running out of ene…