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» The Learning Power of Evolution
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IJCAI
2003
15 years 26 days ago
Understanding the Power of Clause Learning
Efficient implementations of DPLL with the addition of clause learning are the fastest complete satisfiability solvers and can handle many significant real-world problems, such as...
Paul Beame, Henry A. Kautz, Ashish Sabharwal
PPSN
1998
Springer
15 years 3 months ago
On Genetic Algorithms and Lindenmayer Systems
This paper describes a system for simulating the evolution of artificial 2D plant morphologies. Virtual plant genotypes are inspired by the mathematical formalism known as Lindenma...
Gabriela Ochoa
ISVLSI
2008
IEEE
173views VLSI» more  ISVLSI 2008»
15 years 5 months ago
Hermes-GLP: A GALS Network on Chip Router with Power Control Techniques
The evolution of deep submicron technologies allows the development of increasingly complex Systems on a Chip (SoC). However, this evolution is rendering less viable some well-est...
Julian J. H. Pontes, Matheus T. Moreira, Rafael So...
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
15 years 3 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
14 years 11 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay