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Browsing Mathematics by Subject "approximate dynamic programming"

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    MACHINE LEARNING TECHNIQUES APPLIED TO ROBUST OPTIMAL CONTROL PROBLEMS
    (Nazarbayev University School of Sciences and Humanities, 2024-04-19) Zhangunissov, Dilzhan
    This project aims to solve the discrete time stochastic optimal control problem of evaluation of Average Value-at-Risk (AVaR) function. AVaR is an important tool in market risk management used to measure the risk. In the paper it was designed as a sequential decision model and solved by formulating an optimal control problem of minimizing the value. Brute force and Approximate Dynamic Programming (ADP) techniques were used for exact and approximate solutions respectively. Golden section search was used to solve the problem completely. The numerical experiments conducted at the end showed the effectiveness of the algorithm in evaluating the AVaR.
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    ItemOpen Access
    OPTIMAL CONTROL PROBLEM
    (Nazarbayev University School of Sciences and Humanities, 2024-04-15) Kappar, Yerdaulet
    This research paper delves into optimizing the Average Value at Risk (AVaR) using Approximate Dynamic Programming (ADP) in the context of optimal control problems. The study focuses on comparing different numerical optimization methods to achieve that. The methods include Bisection, Gradient Descent, Simulated Annealing, and Conjugate Gradient. The purpose is to assess their accuracy and computational effectiveness in optimizing AVaR function within discrete time, finite horizon settings.