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ICML
2003
IEEE
15 years 10 months ago
Relational Instance Based Regression for Relational Reinforcement Learning
Relational reinforcement learning (RRL) is a Q-learning technique which uses first order regression techniques to generalize the Qfunction. Both the relational setting and the Q-l...
Kurt Driessens, Jan Ramon
QSIC
2008
IEEE
15 years 4 months ago
Using Machine Learning to Refine Black-Box Test Specifications and Test Suites
In the context of open source development or software evolution, developers are often faced with test suites which have been developed with no apparent rationale and which may nee...
Lionel C. Briand, Yvan Labiche, Zaheer Bawar
ECBS
2007
IEEE
188views Hardware» more  ECBS 2007»
14 years 11 months ago
Behavior Analysis-Based Learning Framework for Host Level Intrusion Detection
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
IJCAI
2003
14 years 11 months ago
Multiple-Goal Reinforcement Learning with Modular Sarsa(0)
We present a new algorithm, GM-Sarsa(0), for finding approximate solutions to multiple-goal reinforcement learning problems that are modeled as composite Markov decision processe...
Nathan Sprague, Dana H. Ballard
GPEM
2002
95views more  GPEM 2002»
14 years 9 months ago
On Appropriate Adaptation Levels for the Learning of Gene Linkage
A number of algorithms have been proposed aimed at tackling the problem of learning "Gene Linkage" within the context of genetic optimisation, that is to say, the problem...
James Smith