Results 91 to 100 of about 3,478,919 (201)
Fast Two-Stage Computation of an Index Policy for Multi-Armed Bandits with Setup Delays
Mathematics, 2020 We consider the multi-armed bandit problem with penalties for switching that include setup delays and costs, extending the former results of the author for the special case with no switching delays.
José Niño-Mora
doaj +1 more source
Journal of the Royal Anthropological Institute, Volume 32, Issue 2, Page 554-574, June 2026.The contested dynamics of slum gentrification in Rio de Janeiro came into focus during the brief period of relative peace brought by the pacification policy leading up to the 2016 Olympics. In this unprecedented moment, Rio's South Zone favela residents experienced a respite from the daily confrontations with police operations and drug trade violence ...
Angela Torresan
wiley +1 more source
On Penalization in Stochastic Multi-Armed Bandits
IEEE Transactions on Information TheoryWe study an important variant of the stochastic multi-armed bandit (MAB) problem, which takes penalization into consideration. Instead of directly maximizing cumulative expected reward, we need to balance between the total reward and fairness level.
Guanhua Fang +2 more
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Visualizations for interrogations of multi‐armed bandits
Stat, 2019 A multi‐armed bandit (MAB) algorithm is a sequential experimentation procedure on multiple treatments, which explores their effects and exploits the seemingly optimum treatment. An algorithm is selected for a particular context by evaluating the performances of multiple candidate algorithms in controlling the regret of exploration versus exploitation ...
Timothy J. Keaton, Arman Sabbaghi
openaire +1 more source
Dynamic Pricing With Recommendation and Consumer Feedback
The RAND Journal of Economics, Volume 57, Issue 2, Page 349-367, Summer 2026.ABSTRACT A long‐lived seller sells a new product of unknown value by offering prices and recommendations to short‐lived consumers in continuous time. The seller receives consumer feedback about the product at a rate that increases with the instantaneous sales volume.
Wenji Xu, Shuoguang Yang
wiley +1 more source
Scaling Multi-Armed Bandit Algorithms
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019 The Multi-Armed Bandit (MAB) is a fundamental model capturing the dilemma between exploration and exploitation in sequential decision making. At every time step, the decision maker selects a set of arms and observes a reward from each of the chosen arms. In this paper, we present a variant of the problem, which we call the Scaling MAB (S-MAB): The goal
Fouché, E., Komiyama, J., Böhm, K.
openaire +2 more sources
Neighbor Cell List Optimization in Handover Management Using Cascading Bandits Algorithm
IEEE Access, 2020 Frequent handover is a key challenge in 5G Ultra-Dense Networks (UDN). In this paper, we show the significance of configuring Neighbor Cell List (NCL) in handover procedure.
Chao Wang +5 more
doaj +1 more source
In Situ Characterisation of Hydrogels via Dynamic Interface Printing
Advanced Science, Volume 13, Issue 28, 18 May 2026.ABSTRACT Hydrogels have become pivotal materials for tissue engineering, robotics, biomedical devices, and sensing applications due to their diverse material compositions and tunable mechanical properties. While significant effort has focused on developing novel manufacturing approaches such as extrusion bioprinting and light‐based fabrication methods,
Callum Vidler +2 more
wiley +1 more source
Distributed Exploration in Multi-Armed Bandits
CoRR, 2013 We study exploration in Multi-Armed Bandits in a setting where $k$ players collaborate in order to identify an $ε$-optimal arm. Our motivation comes from recent employment of bandit algorithms in computationally intensive, large-scale applications. Our results demonstrate a non-trivial tradeoff between the number of arm pulls required by each of the ...
Eshcar Hillel +4 more
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Causally Abstracted Multi-armed Bandits
CoRR8 pages, 3 figures (main article); 20 pages, 10 figures (appendix); 40th Conference on Uncertainty in Artificial Intelligence (UAI)
Fabio Massimo Zennaro +6 more
openaire +6 more sources