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AAAI
1994
13 years 8 months ago
Evolving Neural Networks to Focus Minimax Search
Neural networks were evolved through genetic algorithms to focus minimax search in the game of Othello. At each level of the search tree, the focus networks decide which moves are...
David E. Moriarty, Risto Miikkulainen
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
13 years 10 months ago
Growth of self-canceling code in evolutionary systems
This research examines the behavior of inoperative code (introns) in the evolution of genetically robust solutions. Genetically robust solutions are solutions that are less likely...
Xue Zhong, Terence Soule
ICCAD
2001
IEEE
107views Hardware» more  ICCAD 2001»
14 years 3 months ago
A Convex Programming Approach to Positive Real Rational Approximation
As system integration evolves and tighter design constraints must be met, it becomes necessary to account for the non-ideal behavior of all the elements in a system. Certain devic...
Carlos P. Coelho, Joel R. Phillips, Luis Miguel Si...
GECCO
2005
Springer
142views Optimization» more  GECCO 2005»
14 years 6 days ago
Toward evolved flight
We present the first hardware-in-the-loop evolutionary optimization on an ornithopter. Our experiments demonstrate the feasibility of evolving flight through genetic algorithms an...
Rusty Hunt, Gregory Hornby, Jason D. Lohn
GECCO
2005
Springer
118views Optimization» more  GECCO 2005»
14 years 6 days ago
The Push3 execution stack and the evolution of control
The Push programming language was developed for use in genetic and evolutionary computation systems, as the representation within which evolving programs are expressed. It has bee...
Lee Spector, Jon Klein, Maarten Keijzer