thesis
Qualitative analysis of concurrent mean-payoff games
IST Austria Technical Report
published
Krishnendu
Chatterjee
author 2E5DCA20-F248-11E8-B48F-1D18A9856A870000-0002-4561-241X
Rasmus
Ibsen-Jensen
author 3B699956-F248-11E8-B48F-1D18A9856A870000-0003-4783-0389
KrCh
department
We consider concurrent games played by two-players on a finite state graph, where in every round the players simultaneously choose a move, and the current state along with the joint moves determine the successor state. We study the most fundamental objective for concurrent games, namely, mean-payoff or limit-average objective, where a reward is associated to every transition, and the goal of player 1 is to maximize the long-run average of the rewards, and the objective of player 2 is strictly the opposite (i.e., the games are zero-sum). The path constraint for player 1 could be qualitative, i.e., the mean-payoff is the maximal reward, or arbitrarily close to it; or quantitative, i.e., a given threshold between the minimal and maximal reward. We consider the computation of the almost-sure (resp. positive) winning sets, where player 1 can ensure that the path constraint is satisfied with probability 1 (resp. positive probability). Almost-sure winning with qualitative constraint exactly corresponds to the question whether there exists a strategy to ensure that the payoff is the maximal reward of the game. Our main results for qualitative path constraints are as follows: (1) we establish qualitative determinacy results that show for every state either player 1 has a strategy to ensure almost-sure (resp. positive) winning against all player-2 strategies or player 2 has a spoiling strategy to falsify almost-sure (resp. positive) winning against all player-1 strategies; (2) we present optimal strategy complexity results that precisely characterize the classes of strategies required for almost-sure and positive winning for both players; and (3) we present quadratic time algorithms to compute the almost-sure and the positive winning sets, matching the best known bound of the algorithms for much simpler problems (such as reachability objectives). For quantitative constraints we show that a polynomial time solution for the almost-sure or the positive winning set would imply a solution to a long-standing open problem (of solving the value problem of mean-payoff games) that is not known to be in polynomial time.
https://research-explorer.app.ist.ac.at/download/5403/5510/IST-2013-126-v1+1_soda_full.pdf
application/pdfno
IST Austria2013
eng
2664-169010.15479/AT:IST-2013-126-v1-1
33
https://research-explorer.app.ist.ac.at/record/524
Chatterjee, K., & Ibsen-Jensen, R. (2013). <i>Qualitative analysis of concurrent mean-payoff games</i>. IST Austria. <a href="https://doi.org/10.15479/AT:IST-2013-126-v1-1">https://doi.org/10.15479/AT:IST-2013-126-v1-1</a>
Chatterjee, Krishnendu, and Rasmus Ibsen-Jensen. <i>Qualitative Analysis of Concurrent Mean-Payoff Games</i>. IST Austria, 2013. <a href="https://doi.org/10.15479/AT:IST-2013-126-v1-1">https://doi.org/10.15479/AT:IST-2013-126-v1-1</a>.
K. Chatterjee and R. Ibsen-Jensen, <i>Qualitative analysis of concurrent mean-payoff games</i>. IST Austria, 2013.
Chatterjee K, Ibsen-Jensen R. 2013. Qualitative analysis of concurrent mean-payoff games, IST Austria, 33p.
Chatterjee, Krishnendu, and Rasmus Ibsen-Jensen. <i>Qualitative Analysis of Concurrent Mean-Payoff Games</i>. IST Austria, 2013, doi:<a href="https://doi.org/10.15479/AT:IST-2013-126-v1-1">10.15479/AT:IST-2013-126-v1-1</a>.
Chatterjee K, Ibsen-Jensen R. <i>Qualitative Analysis of Concurrent Mean-Payoff Games</i>. IST Austria; 2013. doi:<a href="https://doi.org/10.15479/AT:IST-2013-126-v1-1">10.15479/AT:IST-2013-126-v1-1</a>
K. Chatterjee, R. Ibsen-Jensen, Qualitative Analysis of Concurrent Mean-Payoff Games, IST Austria, 2013.
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