Compact representations of Markov decision processes and their application to printer management. / Representações compactas para processos de decisão de Markov e sua aplicação na adminsitração de impressoras.

AUTOR(ES)

João Vitor Torres

DATA DE PUBLICAÇÃO

2006

RESUMO

Markov Decision Processes (MDPs) are an important tool for planning and optimization in environments under uncertainty. The specification and computational representation of the probability distributions underlying MDPs are central difficulties for their application. This work proposes two strategies for representation of probabilities in a compact and efficient way. These strategies use Bayesian networks and regularities among states and variables. The proposed strategies are particularly useful in systems whose variables have many categories and have strong interrelation. This proposal has been applied to the management of clusters of printers, a real problem that in fact motivated the work. Markov Decision Processes are then used to allow printers to act as a group, and not just individually. The work also presents a comparison between MDPs and Fuzzy Logic in the context of clusters of printers.

ASSUNTO(S)

processos de decisão de markov artificial intelligence markov decision processes printer management administração de impressoras inteligência artificial

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