Topics from this paper
The Complexity of Solving Stochastic Games on Graphs
- Mathematics, Computer ScienceISAAC
A linear time algorithm is exhibited that given a simple stochastic game and the values of all positions of that game, computes a pair of optimal strategies.
The complexity of mean payoff games using universal graphs
- Mathematics, Computer ScienceArXiv
It is shown that separating automata do not yield a quasipolynomial algorithm for solving mean payoff games, and tight bounds on the complexity of algorithms in this class are proved.
Faster algorithms for mean-payoff games
- Computer ScienceFormal Methods Syst. Des.
A new pseudopolynomial algorithm is presented for solving two-player games played on a weighted graph with mean-payoff objective and with energy constraints, improving the best known worst-case complexity for pseudopoly Nominal mean- payoff algorithms.
Value Iteration Using Universal Graphs and the Complexity of Mean Payoff Games
- Mathematics, Computer ScienceMFCS
It is shown that the linear dependence in the exponent in the number k of weights implies that universal graphs do not yield a quasipolynomial time algorithm for solving mean payoff games, implying that tight bounds on the complexity of algorithms formean payoff games using universal graphs are proved.
The Complexity of Ergodic Mean-payoff Games
- Mathematics, Computer ScienceICALP
An optimal exponential bound on the patience of stationary strategies is established and the exact value can be expressed in the existential theory of the reals, and square-root sum hardness is established for a related class of games.
On the computational complexity of solving stochastic mean-payoff games
- Mathematics, Computer ScienceArXiv
We consider some well-known families of two-player, zero-sum, perfect information games that can be viewed as special cases of Shapley's stochastic games. We show that the following tasks are…
The complexity of ergodic games
We study finite-state two-player (zero-sum) concurrent mean-payoff games played on a graph. We focus on the important sub-class of ergodic games where all states are visited infinitely often with…
On strategy improvement algorithms for simple stochastic games
- Computer Science, MathematicsJ. Discrete Algorithms
The computational complexity of a strategy improvement algorithm by Hoffman and Karp for simple stochastic games is studied, and a bound of O(2^n/n) on the convergence time of the Hoffman-Karp algorithm, and the first non-trivial upper bounds on the converge time of these strategy improvement algorithms are proved.
On Strategy Improvement Algorithms for Simple Stochastic Games
- Mathematics, Computer ScienceCIAC
The Hoffman-Karp algorithm converges to optimal strategies of a given SSG, but no nontrivial bounds were previously known on its running time, and a bound of O(2n/n) on the convergence time of this algorithm is shown, and these are the first non-trivial upper bounds on the converge time of these strategy improvement algorithms.
Combinatorial structure and randomized subexponential algorithms for infinite games
- Mathematics, Computer ScienceTheor. Comput. Sci.
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