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NCI
2004
185views Neural Networks» more  NCI 2004»
13 years 8 months ago
Hierarchical reinforcement learning with subpolicies specializing for learned subgoals
This paper describes a method for hierarchical reinforcement learning in which high-level policies automatically discover subgoals, and low-level policies learn to specialize for ...
Bram Bakker, Jürgen Schmidhuber
ICML
1997
IEEE
14 years 7 months ago
Hierarchical Explanation-Based Reinforcement Learning
Explanation-Based Reinforcement Learning (EBRL) was introduced by Dietterich and Flann as a way of combining the ability of Reinforcement Learning (RL) to learn optimal plans with...
Prasad Tadepalli, Thomas G. Dietterich
AAAI
1998
13 years 8 months ago
Learning Investment Functions for Controlling the Utility of Control Knowledge
The utility problem occurs when the cost of the acquired knowledge outweighs its bene ts. When the learner acquires control knowledge for speeding up a problem solver, the bene t ...
Oleg Ledeniov, Shaul Markovitch
JELIA
2010
Springer
13 years 5 months ago
Retroactive Subsumption-Based Tabled Evaluation of Logic Programs
Abstract. Tabled evaluation is a recognized and powerful implementation technique that overcomes some limitations of traditional Prolog systems in dealing with recursion and redund...
Flávio Cruz, Ricardo Rocha
WIDM
2003
ACM
14 years 7 days ago
Query rewriting using views in the presence of inclusion dependencies
Query rewriting using views is an essential issue in data integration. A number of algorithms, e.g., the bucket algorithm, the inverse rules algorithm, the SVB algorithm and the M...
Qingyuan Bai, Jun Hong, Michael F. McTear