RT Conference Proceedings
T1 Multi-objective bandit algorithms with Chebyshev scalarization.
A1 Mandow-Andaluz, Lorenzo
A1 Martín-Albo, Sergio
A1 Pérez-de-la-Cruz-Molina, José Luis
K1 Probabilidades
K1 Toma de decisiones multicriterio
AB In this paper we analyze several alternatives for Chebyshev scalarization  in multi-objective bandit problems. The alternatives are evaluated on a reference bi-objective benchmark problem of Pareto frontier approximation. Performance is analyzed according to three measures: probability of selecting an optimal action, regret, and unfairness. The paper presents a new algorithm that improves the speed of convergence over previous proposals at least by one order of magnitude.
YR 2023
FD 2023
LK https://hdl.handle.net/10630/27987
UL https://hdl.handle.net/10630/27987
LA eng
NO Financiado por Plan Propio de Investigación de la Universidad de Málaga - Campus de Excelencia Internacional Andalucía Tech. L. Mandow supported by project IRIS PID2021-122812OB-I00 (co-financed by FEDER funds). This research is partially supported by the Spanish Ministry of Science and Innovation, the European Regional Development Fund (FEDER), Junta de Andalucía (JA), and Universidad de Málaga (UMA) through the research projects with reference PID2021-122381OB-I00 and UMA20-FEDERJA-065. S. Martín-Albo supported by Beca de Iniciación a la Investigación para estudiantes de grado y máster, I Plan Propio de Investigación y Transferencia de la Universidad de Málaga, España.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 1 mar 2026