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Mathematical Learning Models — Theory and Algorithms [1983]
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The Minimax Risk for the Two-Armed Bandit Problem
- 12
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Bandit Problems with Random Discounting
- 26
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Stochastic Approximation on a Bounded Convex Set
- 33
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Learning Automaton for Finite Semi-Markov Decision Processes
- 43
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A Local Asymptotic Minimax Optimality of an Adaptive Robbins Monro Stochastic Approximation Procedure
- 50
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Dynamic Allocation Indices for Bayesian Bandits
- 68
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The Role of Dynamic Allocation Indices in the Evaluation of Suboptimal Strategies for Families of Bandit Processes
- 78
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On the Discretization Technique for Optimal Discounted Control of the Wiener Process
- 86
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Asymptotic Properties of Learning Models
- 93
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On the infinitesimal characterization of monotone stopping problems in continuous time
- 101
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Numerical Investigation of the Two Armed Bandit
- 108
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Uniform Bounds for a Dynamic Programming Model under Adaptive Control Using Exponentially Bounded Error Probabilities
- 115
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Stochastic Regression Models and Consistency of the Least Squares Identification Scheme
- 126
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Recursive Identification Techniques
- 138
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An Optimization Problem for Matrices with Application to Decision Models
- 145
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On a Class of Learning Algorithms with Symmetric Behavior under Success and Failure
- 156
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Convergence of a General Stochastic Approximation Process under Convex Constraints and some Applications
- 168
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On Kersting’s Theorem on Weak Convergence of Recursions
- 175
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On Continuous Time Learning Models
- 182
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Convergence of Stochastic Approximation Algorithms with Non-Additive Dependent Disturbances and Applications
- 191
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Sequential probability ratio tests for homogeneous Markov chains
- 203
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Allocation Rules for Sequential Clinical Trials
- 213
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Non-Deterministic Modelling and its Application in Adaptive Optimal Control