On ε-Optimality of the Pursuit Learning Algorithm

DOI10.1239/jap/1346955334zbMath1251.68167OpenAlexW3106282232MaRDI QIDQ3165495

Ryan Martin, Omkar Tilak

Publication date: 29 October 2012

Published in: Journal of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.jap/1346955334

zbMATH Keywords

convergencelearning automatonindirect estimator algorithm

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Online algorithms; streaming algorithms (68W27) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)

Related Items (1)

The design of absorbing Bayesian pursuit algorithms and the formal analyses of their \(\varepsilon\)-optimality

Cites Work

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• A new approach to the design of reinforcement schemes for learning automata
• Learning Optimal Discriminant Functions through a Cooperative Game of Automata
• Learning Automata - A Survey
• Probability Inequalities for Sums of Bounded Random Variables
• A Stochastic Approximation Method

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