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FGCS
2010
119views more  FGCS 2010»
13 years 6 months ago
Characterizing fault tolerance in genetic programming
Evolutionary Algorithms, including Genetic Programming (GP), are frequently employed to solve difficult real-life problems, which can require up to days or months of computation. ...
Daniel Lombraña Gonzalez, Francisco Fern&aa...
CEC
2011
IEEE
12 years 8 months ago
Curiosity-driven optimization
— The principle of artificial curiosity directs active exploration towards the most informative or most interesting data. We show its usefulness for global black box optimizatio...
Tom Schaul, Yi Sun, Daan Wierstra, Faustino J. Gom...
ATAL
2009
Springer
14 years 2 months ago
State-coupled replicator dynamics
This paper introduces a new model, i.e. state-coupled replicator dynamics, expanding the link between evolutionary game theory and multiagent reinforcement learning to multistate ...
Daniel Hennes, Karl Tuyls, Matthias Rauterberg
ICANNGA
2007
Springer
153views Algorithms» more  ICANNGA 2007»
14 years 2 months ago
Automatic Design of ANNs by Means of GP for Data Mining Tasks: Iris Flower Classification Problem
This paper describes a new technique for automatically developing Artificial Neural Networks (ANNs) by means of an Evolutionary Computation (EC) tool, called Genetic Programming (G...
Daniel Rivero, Juan R. Rabuñal, Julian Dora...
PPSN
2004
Springer
14 years 1 months ago
Finding Knees in Multi-objective Optimization
Abstract. Many real-world optimization problems have several, usually conflicting objectives. Evolutionary multi-objective optimization usually solves this predicament by searchin...
Jürgen Branke, Kalyanmoy Deb, Henning Dierolf...