73 search results - page 4 / 15 » Incremental Learning of Planning Operators in Stochastic Dom... |
ROBOCUP
2007
Springer
14 years 1 months ago
2007
Springer
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...
JAIR
2010
13 years 5 months ago
2010
Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provide...
ICRA
2008
IEEE
14 years 1 months ago
2008
IEEE
Abstract— This paper describes a novel approach for incremental learning of human motion pattern primitives through on-line observation of human motion. The observed motion time ...
ISRR
2005
Springer
14 years 29 days ago
2005
Springer
ys when planning meant searching for a sequence of abstract actions that satisfied some symbolic predicate. Robots can now learn their own representations through statistical infe...
ECP
1997
Springer
13 years 11 months ago
1997
Springer
Systems that act autonomously in the environment have to be able to integrate three basic behaviors: planning, execution, and learning. Planning involves describing a set of action...