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ECML
2004
Springer
14 years 2 months ago
Model Approximation for HEXQ Hierarchical Reinforcement Learning
HEXQ is a reinforcement learning algorithm that discovers hierarchical structure automatically. The generated task hierarchy repthe problem at different levels of abstraction. In ...
Bernhard Hengst
NIPS
2004
13 years 10 months ago
Brain Inspired Reinforcement Learning
Successful application of reinforcement learning algorithms often involves considerable hand-crafting of the necessary non-linear features to reduce the complexity of the value fu...
François Rivest, Yoshua Bengio, John Kalask...
ICML
2004
IEEE
14 years 9 months ago
Bellman goes relational
Motivated by the interest in relational reinforcement learning, we introduce a novel relational Bellman update operator called ReBel. It employs a constraint logic programming lan...
Kristian Kersting, Martijn Van Otterlo, Luc De Rae...
IJCAI
2007
13 years 10 months ago
Deictic Option Schemas
Deictic representation is a representational paradigm, based on selective attention and pointers, that allows an agent to learn and reason about rich complex environments. In this...
Balaraman Ravindran, Andrew G. Barto, Vimal Mathew
CEEMAS
2005
Springer
14 years 2 months ago
Selection in Scale-Free Small World
Abstract. In this paper we compare our selection based learning algorithm with the reinforcement learning algorithm in Web crawlers. The task of the crawlers is to find new inform...
Zsolt Palotai, Csilla Farkas, András Lö...