EOR
2007
13 years 4 months ago
2007
Performance evaluation of complex systems is a critical issue and bounds computation provides confidence about service quality, reliability, etc. of such systems. The stochastic ...
JSC
2006
13 years 4 months ago
2006
A Viterbi path of length n of a discrete Markov chain is a sequence of n + 1 states that has the greatest probability of ocurring in the Markov chain. We divide the space of all M...
IPL
2006
13 years 4 months ago
2006
In the past 5 years, a series of verification algorithms has been proposed for infinite Markov chains that have a finite attractor, i.e., a set that will be visited infinitely oft...
CORR
2007
Springer
13 years 4 months ago
2007
Springer
We consider qualitative and quantitative verification problems for infinite-state Markov chains. We call a Markov chain decisive w.r.t. a given set of target states F if it almos...
CLEIEJ
2007
13 years 4 months ago
2007
Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
FMSD
2006
13 years 4 months ago
2006
In this paper we present data structures and distributed algorithms for CSL model checking-based performance and dependability evaluation. We show that all the necessary computatio...
CORR
2006
Springer
13 years 4 months ago
2006
Springer
Consider a hidden Markov chain obtained as the observation process of an ordinary Markov chain corrupted by noise. Zuk, et. al. [13, 14] showed how, in principle, one can explicit...
ANOR
2006
13 years 4 months ago
2006
In this paper, we consider a BMAP/G/1 retrial queue with a server subject to breakdowns and repairs, where the life time of the server is exponential and the repair time is general...
CORR
2008
Springer
13 years 4 months ago
2008
Springer
Abstract. This paper presents a novel technique for counterexample generation in probabilistic model checking of Markov chains and Markov Decision Processes. (Finite) paths in coun...
ICML
2010
IEEE
13 years 5 months ago
2010
IEEE
We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...