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CIKM
2007
Springer
14 years 3 months ago
Developing learning strategies for topic-based summarization
Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...
Ouyang You, Sujian Li, Wenjie Li
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
14 years 2 months ago
Learned mutation strategies in genetic programming for evolution and adaptation of simulated snakebot
In this work we propose an approach of incorporating learned mutation strategies (LMS) in genetic programming (GP) employed for evolution and adaptation of locomotion gaits of sim...
Ivan Tanev
ICCBR
2005
Springer
14 years 2 months ago
Learning to Win: Case-Based Plan Selection in a Real-Time Strategy Game
While several researchers have applied case-based reasoning techniques to games, only Ponsen and Spronck (2004) have addressed the challenging problem of learning to win real-time ...
David W. Aha, Matthew Molineaux, Marc J. V. Ponsen
CCGRID
2006
IEEE
14 years 2 months ago
Learning-Based Negotiation Strategies for Grid Scheduling
One of the key requirement for Grid infrastructures is the ability to share resources with nontrivial qualities of service. However, resource management in a decentralized infrast...
Jiadao Li, Ramin Yahyapour
EMO
2009
Springer
159views Optimization» more  EMO 2009»
14 years 3 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel