Strategy iteration is strongly polynomial for 2-player turn-based stochastic games with a constant discount factor
Ye [2011] showed recently that the simplex method with Dantzig's pivoting rule, as well as
Howard's policy iteration algorithm, solve discounted Markov decision processes (MDPs) …
Howard's policy iteration algorithm, solve discounted Markov decision processes (MDPs) …
Reducing blackwell and average optimality to discounted mdps via the blackwell discount factor
J Grand-Clément, M Petrik - Advances in Neural …, 2024 - proceedings.neurips.cc
We introduce the Blackwell discount factor for Markov Decision Processes (MDPs). Classical
objectives for MDPs include discounted, average, and Blackwell optimality. Many existing …
objectives for MDPs include discounted, average, and Blackwell optimality. Many existing …
An ordered approach to solving parity games in quasi polynomial time and quasi linear space
Parity games play an important role in model checking and synthesis. In their paper, Calude
et al. have recently shown that these games can be solved in quasi-polynomial time. We …
et al. have recently shown that these games can be solved in quasi-polynomial time. We …
The mu-calculus and Model Checking
J Bradfield, I Walukiewicz - Handbook of Model Checking, 2018 - Springer
This chapter presents that part of the theory of the μ μ-calculus that is relevant to the model-
checking problem as broadly understood. The μ μ-calculus is one of the most important …
checking problem as broadly understood. The μ μ-calculus is one of the most important …
Synthesis of reactive systems
B Finkbeiner - Dependable Software Systems Engineering, 2016 - ebooks.iospress.nl
These lecture notes trace the developments triggered by Church's classic synthesis problem
from the early solutions in the 1960s to the practical tools that have come out in the past few …
from the early solutions in the 1960s to the practical tools that have come out in the past few …
Subexponential lower bounds for randomized pivoting rules for the simplex algorithm
The simplex algorithm is among the most widely used algorithms for solving linear programs
in practice. With essentially all deterministic pivoting rules it is known, however, to require an …
in practice. With essentially all deterministic pivoting rules it is known, however, to require an …
A subexponential lower bound for Zadeh's pivoting rule for solving linear programs and games
O Friedmann - International Conference on Integer Programming and …, 2011 - Springer
The simplex algorithm is among the most widely used algorithms for solving linear programs
in practice. Most pivoting rules are known, however, to need an exponential number of steps …
in practice. Most pivoting rules are known, however, to need an exponential number of steps …
Stopping criteria for value iteration on stochastic games with quantitative objectives
J Křetínský, T Meggendorfer… - 2023 38th Annual ACM …, 2023 - ieeexplore.ieee.org
A classic solution technique for Markov decision processes (MDP) and stochastic games
(SG) is value iteration (VI). Due to its good practical performance, this approximative …
(SG) is value iteration (VI). Due to its good practical performance, this approximative …
An improved version of the random-facet pivoting rule for the simplex algorithm
The Random-Facet pivoting rule of Kalai and of Matousek, Sharir and Welzl is an elegant
randomized pivoting rule for the simplex algorithm, the classical combinatorial algorithm for …
randomized pivoting rule for the simplex algorithm, the classical combinatorial algorithm for …
The complexity of the simplex method
J Fearnley, R Savani - Proceedings of the forty-seventh annual ACM …, 2015 - dl.acm.org
The simplex method is a well-studied and widely-used pivoting method for solving linear
programs. When Dantzig originally formulated the simplex method, he gave a natural pivot …
programs. When Dantzig originally formulated the simplex method, he gave a natural pivot …