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Online Reinforcement Learning in Markov Decision Process Using Linear Programming
We consider online reinforcement learning in episodic Markov decision process (MDP) with unknown transition function and stochastic rewards drawn from some fixed but unknown distribution.
Online Learning in Budget-Constrained Dynamic Colonel Blotto Games
In this paper, we study the strategic allocation of limited resources using a Colonel Blotto game (CBG) under a dynamic setting and analyze the problem using an online learning approach.
Toward Optimal Adversarial Policies in the Multiplicative Learning System with a Malicious Expert
We consider a learning system based on the conventional multiplicative weight (MW) rule that combines experts' advice to predict a sequence of true outcomes.
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