"Infinite Markov Chains; Expected Reward"@en . . . . . "V\u00FDpo\u010Det st\u0159edn\u00EDch hodnot vybran\u00FDch n\u00E1hodn\u00FDch prom\u011Bnn\u00FDch pro Markovovy \u0159et\u011Bzce s nekone\u010Dn\u011B mnoha stavy"@cs . "14330" . "2"^^ . "Br\u00E1zdil, Tom\u00E1\u0161" . . . "0302-9743" . . . "US - Spojen\u00E9 st\u00E1ty americk\u00E9" . "3821" . "Computing the Expected Accumulated Reward and Gain for a Subclass of Infinite Markov Chains"@en . "2"^^ . "Computing the Expected Accumulated Reward and Gain for a Subclass of Infinite Markov Chains" . "We consider the problem of computing the expected accumulated reward and the average gain per transition in a subclass of Markov chains with countable state spaces where all states are assigned a non-negative reward. We state several abstract conditions that guarantee computability of the above properties up to an arbitrarily small (but non-zero) given error. Finally, we show that our results can be applied to probabilistic lossy channel systems, a well-known model of processes communicating through faulty channels." . . . "RIV/00216224:14330/05:00012779" . . "\u010Cl\u00E1nek se zab\u00FDv\u00E1 problematikou v\u00FDpo\u010Dtu st\u0159edn\u00EDch hodnot pro vybran\u00E9 n\u00E1hodn\u00E9 prom\u011Bnn\u00E9 definovan\u00E9 na b\u011Bz\u00EDch nekone\u010Dn\u011B-stavov\u00FDch Markovov\u00FDch \u0159et\u011Bzc\u016F. Jsou definov\u00E1ny abstraktn\u00ED podm\u00EDnky, za kter\u00FDch je mo\u017Eno uveden\u00E9 hodnoty vypo\u010D\u00EDtat s libovolnou p\u0159esnost\u00ED. Je tak\u00E9 uk\u00E1z\u00E1no, \u017Ee navr\u017Een\u00E1 technika je aplikovateln\u00E1 na pravd\u011Bpodobnostn\u00ED syst\u00E9my s nespolehliv\u00FDmi komunika\u010Dn\u00EDmy kan\u00E1ly."@cs . "2005" . . "Lecture Notes in Computer Science" . "RIV/00216224:14330/05:00012779!RIV08-MSM-14330___" . "Computing the Expected Accumulated Reward and Gain for a Subclass of Infinite Markov Chains" . . . "[57978C16E0CC]" . "372-383" . . "12"^^ . "We consider the problem of computing the expected accumulated reward and the average gain per transition in a subclass of Markov chains with countable state spaces where all states are assigned a non-negative reward. We state several abstract conditions that guarantee computability of the above properties up to an arbitrarily small (but non-zero) given error. Finally, we show that our results can be applied to probabilistic lossy channel systems, a well-known model of processes communicating through faulty channels."@en . "Ku\u010Dera, Anton\u00EDn" . "P(1M0545), P(GA201/03/1161), Z(MSM0021622419)" . "516142" . . "V\u00FDpo\u010Det st\u0159edn\u00EDch hodnot vybran\u00FDch n\u00E1hodn\u00FDch prom\u011Bnn\u00FDch pro Markovovy \u0159et\u011Bzce s nekone\u010Dn\u011B mnoha stavy"@cs . . "Computing the Expected Accumulated Reward and Gain for a Subclass of Infinite Markov Chains"@en . .