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ECAI
2006
Springer
15 years 1 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani
ESANN
2007
14 years 11 months ago
Applying the Episodic Natural Actor-Critic Architecture to Motor Primitive Learning
In this paper, we investigate motor primitive learning with the Natural Actor-Critic approach. The Natural Actor-Critic consists out of actor updates which are achieved using natur...
Jan Peters, Stefan Schaal
ECML
2006
Springer
15 years 1 months ago
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
Scott Proper, Prasad Tadepalli
ML
2002
ACM
133views Machine Learning» more  ML 2002»
14 years 9 months ago
Finite-time Analysis of the Multiarmed Bandit Problem
Reinforcement learning policies face the exploration versus exploitation dilemma, i.e. the search for a balance between exploring the environment to find profitable actions while t...
Peter Auer, Nicolò Cesa-Bianchi, Paul Fisch...
CORR
2007
Springer
73views Education» more  CORR 2007»
14 years 9 months ago
Universal Reinforcement Learning
—We consider an agent interacting with an unmodeled environment. At each time, the agent makes an observation, takes an action, and incurs a cost. Its actions can influence futu...
Vivek F. Farias, Ciamac Cyrus Moallemi, Tsachy Wei...