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DAGM
2006
Springer
13 years 9 months ago
Handling Camera Movement Constraints in Reinforcement Learning Based Active Object Recognition
In real world scenes, objects to be classified are usually not visible from every direction, since they are almost always positioned on some kind of opaque plane. When moving a cam...
Christian Derichs, Heinrich Niemann
ICRA
2006
IEEE
131views Robotics» more  ICRA 2006»
13 years 11 months ago
Using Reinforcement Learning to Improve Exploration Trajectories for Error Minimization
Abstract— The mapping and localization problems have received considerable attention in robotics recently. The exploration problem that drives mapping has started to generate sim...
Thomas Kollar, Nicholas Roy
ICML
2005
IEEE
14 years 6 months ago
Relating reinforcement learning performance to classification performance
We prove a quantitative connection between the expected sum of rewards of a policy and binary classification performance on created subproblems. This connection holds without any ...
John Langford, Bianca Zadrozny
ICML
2002
IEEE
14 years 6 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans
AAAI
2004
13 years 7 months ago
A Qualitative-Quantitative Methods-Based e-Learning Support System in Economic Education
This paper describes a new qualitative-quantitative simulator to help buyers learn how to make decisions when they purchase goods. In this paper, we propose an elearning support s...
Tokuro Matsuo, Takayuki Ito, Toramatsu Shintani