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» An abstraction-based genetic programming system
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GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
14 years 1 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto
ACSC
2009
IEEE
15 years 4 months ago
Inference of Gene Expression Networks Using Memetic Gene Expression Programming
In this paper we aim to infer a model of genetic networks from time series data of gene expression profiles by using a new gene expression programming algorithm. Gene expression n...
Armita Zarnegar, Peter Vamplew, Andrew Stranieri
GPEM
2008
128views more  GPEM 2008»
14 years 9 months ago
Coevolutionary bid-based genetic programming for problem decomposition in classification
In this work a cooperative, bid-based, model for problem decomposition is proposed with application to discrete action domains such as classification. This represents a significan...
Peter Lichodzijewski, Malcolm I. Heywood
DAC
2008
ACM
15 years 10 months ago
Predictive design space exploration using genetically programmed response surfaces
Exponential increases in architectural design complexity threaten to make traditional processor design optimization techniques intractable. Genetically programmed response surface...
Henry Cook, Kevin Skadron
GECCO
2006
Springer
202views Optimization» more  GECCO 2006»
15 years 1 months ago
Evolving hash functions by means of genetic programming
The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fa...
César Estébanez, Julio César ...