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» Learning to generalize for complex selection tasks
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LAMAS
2005
Springer
14 years 6 days ago
Multi-agent Relational Reinforcement Learning
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
TEC
2002
133views more  TEC 2002»
13 years 6 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben
ICSE
2008
IEEE-ACM
14 years 6 months ago
Creating a cognitive metric of programming task difficulty
Conducting controlled experiments about programming activities often requires the use of multiple tasks of similar difficulty. In previously reported work about a controlled exper...
Brian de Alwis, Gail C. Murphy, Shawn Minto
NAACL
2007
13 years 8 months ago
A Systematic Exploration of the Feature Space for Relation Extraction
Relation extraction is the task of finding semantic relations between entities from text. The state-of-the-art methods for relation extraction are mostly based on statistical lea...
Jing Jiang, ChengXiang Zhai
EWCBR
2006
Springer
13 years 10 months ago
Rough Set Feature Selection Algorithms for Textual Case-Based Classification
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Kalyan Moy Gupta, David W. Aha, Philip Moore