RT Journal Article
T1 Multi-objective dynamic programming with limited precision
A1 Mandow-Andaluz, Lorenzo
A1 Pérez-de-la-Cruz-Molina, José Luis
A1 Pozas García, Nicolás
K1 Programación dinámica
AB This paper addresses the problem of approximating the set of all solutions for Multi-objective Markov Decision Processes. We show that in the vast majority of interesting cases, the number of solutions is exponential or even infinite. In order to overcome this difficulty we propose to approximate the set of all solutions by means of a limited precision approach based on White’s multi-objective value-iteration dynamic programming algorithm. We prove that the number of calculated solutions is tractable and show experimentally that the solutions obtained are a good approximation of the true Pareto front.
PB Springer
YR 2021
FD 2021-11-02
LK https://hdl.handle.net/10630/24040
UL https://hdl.handle.net/10630/24040
LA eng
NO Mandow, L., Perez-de-la-Cruz, J.L. & Pozas, N. Multi-objective dynamic programming with limited precision. J Glob Optim 82, 595–614 (2022). https://doi.org/10.1007/s10898-021-01096-x
NO Funding for open access charge: Universidad de Málaga / CBUA. Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Funded by the Spanish Government, Agencia Estatal de Investigación (AEI) and European Union, Fondo Europeo de Desarrollo Regional (FEDER), Grant TIN2016-80774-R (AEI/FEDER, UE).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 3 mar 2026