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Feature Adaptation Algorithms for Reinforcement Learning with Applications to Wireless Sensor Networks And Road Traffic Control
(2017-09-20)
Many sequential decision making problems under uncertainty arising in engineering, science and economics are often modelled as Markov Decision Processes (MDPs). In the setting of MDPs, the goal is to and a state dependent ...
Resource Allocation for Sequential Decision Making Under Uncertainaty : Studies in Vehicular Traffic Control, Service Systems, Sensor Networks and Mechanism Design
(2017-11-27)
A fundamental question in a sequential decision making setting under uncertainty is “how to allocate resources amongst competing entities so as to maximize the rewards accumulated in the long run?”. The resources allocated ...
Optimization Algorithms for Deterministic, Stochastic and Reinforcement Learning Settings
(2018-05-30)
Optimization is a very important field with diverse applications in physical, social and biological sciences and in various areas of engineering. It appears widely in ma-chine learning, information retrieval, regression, ...
Approximate Dynamic Programming and Reinforcement Learning - Algorithms, Analysis and an Application
(2018-08-13)
Problems involving optimal sequential making in uncertain dynamic systems arise in domains such as engineering, science and economics. Such problems can often be cast in the framework of Markov Decision Process (MDP). ...