New algorithm BLINQ learns Whittle indices for Markov Decision Processes

Researchers have developed BLINQ, a novel model-based algorithm designed to learn Whittle indices for Markov Decision Processes. This new approach constructs an empirical estimate of the MDP and then computes the indices, offering a proven convergence guarantee and a bound on learning time. Numerical experiments indicate BLINQ requires fewer samples than existing Q-learning methods for accurate approximations and has a lower overall computational cost. AI

RANK_REASON This is a research paper detailing a new algorithm for learning Whittle indices in MDPs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

• Joël Charles-Rebuffé
• Markov Decision Process
• Q-learning
• Whittle indices

• paper
• other

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