Skip navigation
Skip navigation

Context tree maximizing reinforcement learning

Nguyen, Phuong; Sunehag, Peter; Hutter, Marcus

Description

Recent developments in reinforcement learning for nonMarkovian problems witness a surge in history-based methods, among which we are particularly interested in two frameworks, ΦMDP and MC-AIXI-CTW. ΦMDP attempts to reduce the general RL problem, where the environment’s states and dynamics are both unknown, to an MDP, while MCAIXI-CTW incrementally learns a mixture of context trees as its environment model. The main idea of ΦMDP is to connect generic reinforcement learning with classical...[Show more]

CollectionsANU Research Publications
Date published: 2012-07
Type: Conference paper
URI: http://hdl.handle.net/1885/14729

Download

File Description SizeFormat Image
Nguyen et al Context Tree Maximizing 2012.pdf501.87 kBAdobe PDFThumbnail


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  12 November 2018/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator