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GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 1 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
55
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GECCO
2006
Springer
124views Optimization» more  GECCO 2006»
15 years 1 months ago
Genetic programming for human oral bioavailability of drugs
Automatically assessing the value of bioavailability from the chemical structure of a molecule is a very important issue in biomedicine and pharmacology. In this paper, we present...
Francesco Archetti, Stefano Lanzeni, Enza Messina,...
73
Voted
GECCO
2006
Springer
168views Optimization» more  GECCO 2006»
15 years 1 months ago
3D airspace sectoring by evolutionary computation: real-world applications
This paper presents a new method for 3D cutting of geometrical space with application to airspace sectoring. This problem comes from the air traffic management but the proposed me...
Daniel Delahaye, Stephane Puechmorel
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
15 years 1 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
15 years 1 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon