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ICML
1998
IEEE
14 years 8 months ago
Genetic Programming and Deductive-Inductive Learning: A Multi-Strategy Approach
Genetic Programming (GP) is a machine learning technique that was not conceived to use domain knowledge for generating new candidate solutions. It has been shown that GP can bene ...
Ricardo Aler, Daniel Borrajo, Pedro Isasi
CEC
2010
IEEE
13 years 5 months ago
Active Learning Genetic programming for record deduplication
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...
GECCO
2004
Springer
110views Optimization» more  GECCO 2004»
14 years 28 days ago
Using GP to Model Contextual Human Behavior
To create a realistic environment, some simulations require simulated agents with human behavior pattern. Creating such agents with realistic behavior can be a tedious and time con...
Hans Fernlund, Avelino J. Gonzalez
EUROGP
2001
Springer
105views Optimization» more  EUROGP 2001»
14 years 1 days ago
Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems
Abstract. In this paper we continue our study on adaptive genetic programming. We use Stepwise Adaptation of Weights (saw) to boost performance of a genetic programming algorithm o...
Jeroen Eggermont, Jano I. van Hemert
EUROGP
2007
Springer
175views Optimization» more  EUROGP 2007»
14 years 1 months ago
Fast Genetic Programming on GPUs
As is typical in evolutionary algorithms, fitness evaluation in GP takes the majority of the computational effort. In this paper we demonstrate the use of the Graphics Processing...
Simon Harding, Wolfgang Banzhaf