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» On Genetic Algorithms and Lindenmayer Systems
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ICANN
1997
Springer
15 years 10 months ago
Minimalistic Approach to 3D Obstacle Avoidance Behavior from Simulated Evolution
We present a minimalistic approach to establish obstacle avoidance and course stabilization behavior of a simulated flying autonomous agent in a 3D virtual world. The agent uses v...
Titus R. Neumann, Susanne A. Huber, Heinrich H. B&...
EUROGP
2007
Springer
143views Optimization» more  EUROGP 2007»
15 years 10 months ago
Confidence Intervals for Computational Effort Comparisons
Abstract. When researchers make alterations to the genetic programming algorithm they almost invariably wish to measure the change in performance of the evolutionary system. No one...
Matthew Walker, Howard Edwards, Chris H. Messom
SP
2000
IEEE
15 years 10 months ago
Searching for a Solution: Engineering Tradeoffs and the Evolution of Provably Secure Protocols
Tradeoffs are an important part of engineering security. Protocol security is important. So are efficiency and cost. This paper provides an early framework for handling such aspec...
John A. Clark, Jeremy L. Jacob
IPPS
2007
IEEE
16 years 18 days ago
Optimizing Sorting with Machine Learning Algorithms
The growing complexity of modern processors has made the development of highly efficient code increasingly difficult. Manually developing highly efficient code is usually expen...
Xiaoming Li, María Jesús Garzar&aacu...
GECCO
2004
Springer
164views Optimization» more  GECCO 2004»
15 years 11 months ago
Fuzzy Dominance Based Multi-objective GA-Simplex Hybrid Algorithms Applied to Gene Network Models
Hybrid algorithms that combine genetic algorithms with the Nelder-Mead simplex algorithm have been effective in solving certain optimization problems. In this article, we apply a s...
Praveen Koduru, Sanjoy Das, Stephen Welch, Judith ...