Title :
Solving Partial-Information Stochastic Parity Games
Author :
Nain, Sumit ; Vardi, Moshe Y.
Author_Institution :
Dept. of Comput. Sci., Rice Univ., Houston, TX, USA
Abstract :
We study one-sided partial-information 2-player concurrent stochastic games with parity objectives. In such a game, one of the players has only partial visibility of the state of the game, while the other player has complete knowledge. In general, such games are known to be undecidable, even for the case of a single player (POMDP). These undecidability results depend crucially on player strategies that exploit an infinite amount of memory. However, in many applications of games, one is usually more interested in finding a finite-memory strategy. We consider the problem of whether the player with partial information has a finite-memory winning strategy when the player with complete information is allowed to use an arbitrary amount of memory. We show that this problem is decidable.
Keywords :
decidability; stochastic games; POMDP; complete information player; decidability; finite-memory winning strategy; one-sided partial-information 2-player concurrent stochastic parity games; partial information player; player strategy; undecidability; Automata; Games; Markov processes; Memory management; Probabilistic logic; Transducers; Alternating tree automata; Finite-memory strategy; Partial-observation games; Stochastic games;
Conference_Titel :
Logic in Computer Science (LICS), 2013 28th Annual IEEE/ACM Symposium on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4799-0413-6
DOI :
10.1109/LICS.2013.40