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EUROGP
2006
Springer
140views Optimization» more  EUROGP 2006»
13 years 11 months ago
Evolving Noisy Oscillatory Dynamics in Genetic Regulatory Networks
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation...
André Leier, P. Dwight Kuo, Wolfgang Banzha...
TEC
2008
135views more  TEC 2008»
13 years 7 months ago
Quantum Genetic Optimization
Abstract--The complexity of the selection procedure of a genetic algorithm that requires reordering, if we restrict the class of the possible fitness functions to varying fitness f...
Andrea Malossini, Enrico Blanzieri, T. Calarco
PDPTA
2003
13 years 9 months ago
Java Resources for Teaching Reinforcement Learning
— In this paper we present a library of classes for programming reinforcement learning simulations in Java. This library is based upon the standard by Sutton and Santamaria [1], ...
Amy J. Kerr, Todd W. Neller, Christopher J. La Pil...
GPEM
2007
116views more  GPEM 2007»
13 years 7 months ago
Using evolvable genetic cellular automata to model breast cancer
Cancer is an evolutionary process; mutated cells are selected for abnormal growth and survivability. Here, a computer simulation is used to model ductal carcinoma in situ (DCIS), ...
Armand Bankhead, Robert B. Heckendorn
IJIT
2004
13 years 9 months ago
"Intuition" Operator: Providing Genomes with Reason
In this contribution, the use of a new genetic operator is proposed. The main advantage of using this operator is that it is able to assist the evolution procedure to converge fast...
Grigorios N. Beligiannis, Georgios A. Tsirogiannis...