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ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
15 years 6 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
BMCBI
2010
161views more  BMCBI 2010»
15 years 16 days ago
CGHpower: exploring sample size calculations for chromosomal copy number experiments
Background: Determining a suitable sample size is an important step in the planning of microarray experiments. Increasing the number of arrays gives more statistical power, but ad...
Ilari Scheinin, Jose A. Ferreira, Sakari Knuutila,...
ECAI
2006
Springer
15 years 4 months ago
Learning Behaviors Models for Robot Execution Control
Robust execution of robotic tasks is a difficult problem. In many situations, these tasks involve complex behaviors combining different functionalities (e.g. perception, localizat...
Guillaume Infantes, Félix Ingrand, Malik Gh...
109
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ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 6 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
AH
2000
Springer
15 years 4 months ago
A Connectionist Approach for Supporting Personalized Learning in a Web-Based Learning Environment
The paper investigates the use of computational intelligence for adaptive lesson presentation in a Web-based learning environment. A specialized connectionist architecture is devel...
Kyparisia A. Papanikolaou, George D. Magoulas, Mar...