This repo contains my assignments/projects of the MVA Reinforcement-learning course. This course introduce the models and mathematical tools used in formalizing the problem of learning and decision-making under uncertainty, with particular focus on the frameworks of reinforcement learning and multi-arm bandit. I got 17/20 at the end of this course
Topics:
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Historical multi-disciplinary basis of reinforcement learning
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Markov decision processes and dynamic programming
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Stochastic approximation and Monte-Carlo methods
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Function approximation and statistical learning theory
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Approximate dynamic programming
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Introduction to stochastic and adversarial multi-arm bandit
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Learning rates and finite-sample analysis