| Texto completo | |
| Autor(es): |
Freire, Valdinei
;
Delgado, Karina Valdivia
;
IEEE
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | PROCEEDINGS OF 2016 5TH BRAZILIAN CONFERENCE ON INTELLIGENT SYSTEMS (BRACIS 2016); v. N/A, p. 6-pg., 2016-01-01. |
| Resumo | |
The Goal-Directed Risk-Sensitive Markov Decision Process allows arbitrary risk attitudes for the probabilistic planning problem to reach a goal state. In this problem, the risk attitude is modeled by an expected exponential utility and a risk factor lambda. However, the problem is not well defined for every lambda, posing the problem of defining the maximum (extreme) value for this factor. In this paper, we propose an algorithm to find this epsilon-extreme risk factor and the corresponding optimal policy. (AU) | |
| Processo FAPESP: | 15/01587-0 - Armazenagem, modelagem e análise de sistemas dinâmicos para aplicações em e-Science |
| Beneficiário: | João Eduardo Ferreira |
| Modalidade de apoio: | Auxílio à Pesquisa - Programa eScience e Data Science - Temático |