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IJCAI
2007
13 years 9 months ago
Utile Distinctions for Relational Reinforcement Learning
We introduce an approach to autonomously creating state space abstractions for an online reinforcement learning agent using a relational representation. Our approach uses a tree-b...
William Dabney, Amy McGovern
ILP
2003
Springer
14 years 27 days ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon
ICML
2003
IEEE
14 years 8 months ago
Tractable Bayesian Learning of Tree Augmented Naive Bayes Models
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
Jesús Cerquides, Ramon López de M&aa...
IROS
2006
IEEE
165views Robotics» more  IROS 2006»
14 years 1 months ago
Learning Relational Navigation Policies
— Navigation is one of the fundamental tasks for a mobile robot. The majority of path planning approaches has been designed to entirely solve the given problem from scratch given...
Alexandru Cocora, Kristian Kersting, Christian Pla...
JMLR
2006
113views more  JMLR 2006»
13 years 7 months ago
Generalized Bradley-Terry Models and Multi-Class Probability Estimates
The Bradley-Terry model for obtaining individual skill from paired comparisons has been popular in many areas. In machine learning, this model is related to multi-class probabilit...
Tzu-Kuo Huang, Ruby C. Weng, Chih-Jen Lin