Results 51 to 60 of about 3,478,919 (201)
Multi-Armed Bandits Convergence Acceleration Using Cluster Normalizations
IEEE AccessRecommender systems usually operate in non-stationary environments, so the standard techniques used to create recommendations begin to degrade after some use.
Victoria Strenadko +2 more
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Context-aware Multi-stakeholder Recommender Systems
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Traditional recommender systems help users find the most relevant products or services to match their needs and preferences. However, they overlook the preferences of other sides of the market (aka stakeholders) involved in the system.
Tahereh Arabghalizi +1 more
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Highly Configurable Evolutionary Multi‐Objective Optimisation and Application in UAV Path Planning
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Multi‐objective optimisation is crucial in engineering and real‐world decision‐making. Although traditional decomposition‐based approaches such as MOEA/D yield reasonable results, they depend heavily on expert knowledge. Existing MetaBBO approaches partially alleviate this reliance, however, they offer limited configurability and lack real ...
Kaixu Chen +4 more
wiley +1 more source
On-Line Adaptation of Exploration in the One-Armed Bandit with Covariates Problem
, 2010 Many sequential decision making problems require an agent to balance exploration and exploitation to maximise long-term reward. Existing policies that address this tradeoff typically have parameters that are set a priori to control the amount of ...
Niall M. Adams +8 more
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Adaptive Noise Exploration for Neural Contextual Multi-Armed Bandits
AlgorithmsIn contextual multi-armed bandits, the relationship between contextual information and rewards is typically unknown, complicating the trade-off between exploration and exploitation.
Chi Wang, Lin Shi, Junru Luo
doaj +1 more source
History, EarlyView.Abstract This article examines the poll tax (Ottoman Turkish cizye; Arabic jizya) levied on non‐Muslim subjects of the Ottoman Empire, not as a fixed, one‐dimensional tax item within the Ottoman fiscal system but as a multi‐layered administrative instrument organized around obligation, exemption and remission.
ÖZLEM BAŞARIR
wiley +1 more source
Optimizing the ε Parameter in ε-Greedy Strategy for Multi-Armed Bandits [PDF]
ITM Web of ConferencesWith the widespread adoption of the internet, online advertising has grown exponentially. To enhance ad recommendation efficiency, various Multi-Armed Bandit (MAB) algorithms have been deployed. Among these, the Thompson ε-Greedy algorithm integrates the
Jiang Haotong
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Algorithmic Monoculture and Its Critics
Philosophical Perspectives, EarlyView.ABSTRACT Algorithmic decision‐making is replacing idiosyncratic human judgment in domains such as hiring, lending, and criminal justice. This shift promises increased consistency, but many scholars worry that it can go too far. They warn of the dangers of algorithmic monoculture, in which all decisions across a domain are made using a single algorithm.
Brian Hedden, Manish Raghavan
wiley +1 more source
Skyline Identification in Multi-Arm Bandits
2018 IEEE International Symposium on Information Theory (ISIT), 2018 We introduce a variant of the classical PAC multi-armed bandit problem. There is an ordered set of $n$ arms $A[1],\dots,A[n]$, each with some stochastic reward drawn from some unknown bounded distribution. The goal is to identify the $skyline$ of the set $A$, consisting of all arms $A[i]$ such that $A[i]$ has larger expected reward than all lower ...
Albert Cheu +2 more
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Budget-limited multi-armed bandits [PDF]
, 2012 Decision making under uncertainty is one of the most important challenges within the research field of artificial intelligence, as they present many everyday situations that agents have to face.
Tran-Thanh, Long
core +1 more source