In this research note, we revisit the bandits with expert advice problem. Under a restricted feedback model, we prove a lower bound of order (Formula presented) for the worst-case regret, where K is the number of actions, N > K the number of experts, and T the time horizon. This matches a previously known upper bound of the same order and improves upon the best available lower bound of (Formula presented). For the standard feedback model, we prove a new instance-based upper bound that depends on the agreement between the experts and provides a logarithmic improvement compared to prior results.

Improved Regret Bounds for Bandits with Expert Advice / N. Cesa Bianchi, K. Eldowa, E. Esposito, J. Olkhovskaya. - In: JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH. - ISSN 1943-5037. - 83:(2025 Jul), pp. 6.1-6.14. [10.1613/jair.1.16738]

Improved Regret Bounds for Bandits with Expert Advice

N. Cesa Bianchi
Primo
;
K. Eldowa
Secondo
;
E. Esposito
Penultimo
;
2025

Abstract

In this research note, we revisit the bandits with expert advice problem. Under a restricted feedback model, we prove a lower bound of order (Formula presented) for the worst-case regret, where K is the number of actions, N > K the number of experts, and T the time horizon. This matches a previously known upper bound of the same order and improves upon the best available lower bound of (Formula presented). For the standard feedback model, we prove a new instance-based upper bound that depends on the agreement between the experts and provides a logarithmic improvement compared to prior results.
English
Settore INFO-01/A - Informatica
Articolo
Esperti anonimi
Ricerca di base
Pubblicazione scientifica
   Algorithms, Games, and Digital Markets (ALGADIMAR)
   ALGADIMAR
   MINISTERO DELL'ISTRUZIONE E DEL MERITO
   2017R9FHSR_006

   European Lighthouse of AI for Sustainability (ELIAS)
   ELIAS
   EUROPEAN COMMISSION
   101120237
lug-2025
AI Access Foundation
83
6
1
14
14
Pubblicato
Periodico con rilevanza internazionale
https://www.jair.org/index.php/jair/article/view/16738/27186
DSRC - Data science research center
manual
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info:eu-repo/semantics/article
Improved Regret Bounds for Bandits with Expert Advice / N. Cesa Bianchi, K. Eldowa, E. Esposito, J. Olkhovskaya. - In: JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH. - ISSN 1943-5037. - 83:(2025 Jul), pp. 6.1-6.14. [10.1613/jair.1.16738]
open
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262
Article (author)
Periodico con Impact Factor
N. Cesa Bianchi, K. Eldowa, E. Esposito, J. Olkhovskaya
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1176015
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