We analyse the probability 1 − δ to be in an optimum solution after k steps of an inhomogeneous Markov chain which is specified by a logarithmic cooling schedule c(k) = Γ/ ln ...
Decisionand optimizationproblemsinvolvinggraphsarise in manyareas of artificial intelligence, including probabilistic networks, robot navigation, and network design. Manysuch prob...
We propose an approach to lossy source coding, utilizing ideas from Gibbs sampling, simulated annealing, and Markov Chain Monte Carlo (MCMC). The idea is to sample a reconstructio...
Failure diagnosis in large and complex systems is a critical task. A discrete event system (DES) approach to the problem of failure diagnosis is presented in this paper. A classic...
Calin Ciufudean, Adrian Graur, Constantin Filote, ...
High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...