Results 81 to 90 of about 492,986 (210)

Multilevel Constrained Bandits: A Hierarchical Upper Confidence Bound Approach with Safety Guarantees

Mathematics
The multi-armed bandit (MAB) problem is a foundational model for sequential decision-making under uncertainty. While MAB has proven valuable in applications such as clinical trials and online advertising, traditional formulations have limitations ...
Ali Baheri
doaj   +1 more source

Unpacking student interactions in GenAI‐assisted social annotation: An epistemic network analysis of cognitive and social presence

British Journal of Educational Technology, EarlyView.
Abstract Cognitive presence and social presence are essential for computer‐supported collaborative learning (CSCL). Yet, monitoring and providing personalised feedback to support these presences remain a persistent challenge, particularly in the context of social annotation (SA).
Mengru Pan, Chun Lai, Kai Guo, Chin‐Hsi Lin   +3 more
wiley   +1 more source

LLM-Guided Ensemble Learning for Contextual Bandits with Copula and Gaussian Process Models

Mathematics
Contextual multi-armed bandits (CMABs) are vital for sequential decision-making in areas such as recommendation systems, clinical trials, and finance. We propose a simulation framework integrating Gaussian Process (GP)-based CMABs with vine copulas to ...
Jong-Min Kim
doaj   +1 more source

Online‐optimized RAG for tool use and function calling

Decision Sciences, EarlyView.
Abstract In many applications, retrieval‐augmented generation (RAG) drives tool use and function calling by embedding the (user) queries and matching them to prespecified tool/function descriptions. In this article, we address an embedding misalignment issue that often arises in practical applications due to imperfect embedding models or noisy ...
Yu Pan, Xiaocheng Li, Hanzhao Wang
wiley   +1 more source

Diffusion Models Meet Contextual Bandits

International audienceEfficient online decision-making in contextual bandits is challenging, as methods without informative priors often suffer from computational or statistical inefficiencies.
Aouali, Imad
core   +4 more sources

Adaptive Decision-Making in Audio Classification: A Systematic Review of Reinforcement Learning and Multi-Armed Bandit Frameworks

Machine Learning and Knowledge Extraction
Adaptive decision-making has emerged as an important direction in audio classification. Reinforcement learning (RL) and multi-armed bandit (MAB) methods offer principled frameworks for sequential and localized decision-making.
Geofrey Owino, Timothy Kamanu, John Ndiritu   +2 more
doaj   +1 more source

Evidence Gathering Under Competitive and Noncompetitive Rewards

Journal of Economics &Management Strategy, EarlyView.
ABSTRACT Reward schemes may affect not only agents' effort but also their incentives to gather information in order to reduce the riskiness of the productive activity. In a laboratory experiment using a novel task, we find that the relationship between incentives and evidence gathering depends critically on the availability of information about peers ...
Philip Brookins, Jennifer Brown, Dmitry Ryvkin   +2 more
wiley   +1 more source

$\alpha$-Fair Contextual Bandits [PDF]

, 2023
Contextual bandit algorithms are at the core of many applications, including recommender systems, clinical trials, and optimal portfolio selection. One of the most popular problems studied in the contextual bandit literature is to maximize the sum of the
Chaudhary, Siddhant, Sinha, Abhishek
core  

Dynamic Batch Learning in High-Dimensional Sparse Linear Contextual Bandits [PDF]

, 2022
We study the problem of dynamic batch learning in high-dimensional sparse linear contextual bandits, where a decision maker, under a given maximum-number-of-batch constraint and only able to observe rewards at the end of each batch, can dynamically ...
Zhou, Zhengyuan, Ren, Zhimei
core   +1 more source

Making Boundaries: Polish Memory, Identity and the Ukrainian Other

Nations and Nationalism, EarlyView.
ABSTRACT Political elites use historical references abundantly when drawing national boundaries. Despite the prominence of such language, we know little about the ways in which ordinary citizens internalise historical narratives of the Other to construct their national identity.
Félix Krawatzek
wiley   +1 more source