Algoritmos eficientes para tomada de decisão sob incerteza baseada em grafos
- Auxílios pontuais (curta duração)
Texto completo | |
Autor(es): |
Número total de Autores: 2
|
Afiliação do(s) autor(es): | [1] Univ Sao Paulo, Inst Matemat & Estat, BR-05508090 Sao Paulo - Brazil
[2] Univ Sao Paulo, Escola Politecn, BR-05508030 Sao Paulo - Brazil
Número total de Afiliações: 2
|
Tipo de documento: | Artigo Científico |
Fonte: | INTERNATIONAL JOURNAL OF APPROXIMATE REASONING; v. 68, p. 230-245, JAN 2016. |
Citações Web of Science: | 1 |
Resumo | |
Limited memory influence diagrams are graph-based models that describe decision problems with limited information such as planning with teams and/or agents with imperfect recall. Solving a (limited memory) influence diagram is an NP-hard problem, often approached through local search. In this work we give a closer look at k-neighborhood local search approaches. We show that finding a k-neighboring strategy that improves on the current solution is W{[}1]-hard and hence unlikely to be polynomial-time tractable. We also show that finding a strategy that resembles an optimal strategy (but may have low expected utility) is NP-hard. We then develop fast schema to perform approximate k-local search; experiments show that our methods improve on current local search algorithms both with respect to time and to accuracy. (C) 2015 Elsevier Inc. All rights reserved. (AU) | |
Processo FAPESP: | 13/23197-4 - Algoritmos eficientes para tomada de decisão sob incerteza baseada em grafos |
Beneficiário: | Denis Deratani Mauá |
Linha de fomento: | Bolsas no Brasil - Pós-Doutorado |