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GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
13 years 11 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...
SAIG
2000
Springer
13 years 11 months ago
On Jones-Optimal Specialization for Strongly Typed Languages
The phrase optimal program specialization" was de ned by Jones et al. in 1993 to capture the idea of a specializer being strong enough to remove entire layers of interpretatio...
Henning Makholm
AIPS
2008
13 years 10 months ago
HiPPo: Hierarchical POMDPs for Planning Information Processing and Sensing Actions on a Robot
Flexible general purpose robots need to tailor their visual processing to their task, on the fly. We propose a new approach to this within a planning framework, where the goal is ...
Mohan Sridharan, Jeremy L. Wyatt, Richard Dearden
FOGA
1998
13 years 9 months ago
Understanding Interactions among Genetic Algorithm Parameters
Genetic algorithms (GAs) are multi-dimensional and stochastic search methods, involving complex interactions among their parameters. For last two decades, researchers have been tr...
Kalyanmoy Deb, Samir Agrawal
BMCBI
2010
142views more  BMCBI 2010»
13 years 8 months ago
pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree
Background: Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-ba...
Frederick A. Matsen III, Robin B. Kodner, E. Virgi...