Mathematical Learning Models - Theory and Algorithms: Lecture Notes in Statistics, cartea 20
Editat de U. Herkenrath, D. Kalin, W. Vogelen Limba Engleză Paperback – 27 sep 1983
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Specificații
ISBN-13: 9780387909134
ISBN-10: 0387909133
Pagini: 244
Ilustrații: XIII, 226 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.38 kg
Ediția:Softcover reprint of the original 1st ed. 1983
Editura: Springer
Colecția Lecture Notes in Statistics
Seria Lecture Notes in Statistics
Locul publicării:New York, NY, United States
ISBN-10: 0387909133
Pagini: 244
Ilustrații: XIII, 226 p.
Dimensiuni: 155 x 235 x 14 mm
Greutate: 0.38 kg
Ediția:Softcover reprint of the original 1st ed. 1983
Editura: Springer
Colecția Lecture Notes in Statistics
Seria Lecture Notes in Statistics
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
The Minimax Risk for the Two-Armed Bandit Problem.- Bandit Problems with Random Discounting.- Stochastic Approximation on a Bounded Convex Set.- Learning Automaton for Finite Semi-Markov Decision Processes.- A Local Asymptotic Minimax Optimality of an Adaptive Robbins-Monro Stochastic Approximation Procedure.- Dynamic Allocation Indices for Bayesian Bandits.- The Role of Dynamic Allocation Indices in the Evaluation of Suboptimal Strategies for Families of Bandit Processes.- On the Discretization Technique for Optimal Discounted Control of the Wiener Process.- Asymptotic Properties of Learning Models.- On the Infinitesimal Characterization of Monotone Stopping Problems in Continuous Time.- Numerical Investigation of the Two-Armed Bandit.- Uniform Bounds for a Dynamic Programming Model under Adaptive Control Using Exponentially Bounded Error Probabilities.- Stochastic Regression Models and Consistency of the Least Squares Identification Scheme.- Recursive Identification Techniques.- An Optimization Problem for Matrices with Application to Decision Models.- On a Class of Learning Algorithms with Symmetric Behavior under Success and Failure.- Convergence of a General Stochastic Approximation Process under Convex Constraints and Some Applications.- On Kersting’s Theorem on Weak Convergence of Recursions.- On Continuous Time Learning Models.- Convergence of Stochastic Approximation Algorithms with Non-Additive Dependent Disturbances and Applications.- Sequential Probability Ratio Tests for Homogeneous Markov Chains.- Allocation Rules for Sequential Clinical Trials.- Non-Deterministic Modelling and its Application in Adaptive Optimal Control.