Sciweavers

Share
ICML
2005
IEEE

A theoretical analysis of Model-Based Interval Estimation

9 years 5 months ago
A theoretical analysis of Model-Based Interval Estimation
Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Interval Estimation (MBIE) learns efficiently in practice, effectively balancing exploration and exploitation. This paper presents the first theoretical analysis of MBIE, proving its efficiency even under worst-case conditions. The paper also introduces a new performance metric, average loss, and relates it to its less "online" cousins from the literature.
Alexander L. Strehl, Michael L. Littman
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2005
Where ICML
Authors Alexander L. Strehl, Michael L. Littman
Comments (0)
books