Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
An Evolved Circuit, Intrinsic in Silicon, Entwined with Physics
ICES '96 Proceedings of the First International Conference on Evolvable Systems: From Biology to Hardware
The Convergence of the Abstract Evolutionary Algorithm Based on a Special Selection Mechanism
ICCIMA '03 Proceedings of the 5th International Conference on Computational Intelligence and Multimedia Applications
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Automated Antenna Design Using Normalized Steady State Genetic Algorithm
AHS '08 Proceedings of the 2008 NASA/ESA Conference on Adaptive Hardware and Systems
Evolvable hardware: using evolutionary computation to design and optimize hardware systems
IEEE Computational Intelligence Magazine
Autonomous evolution of dynamic gaits with two quadruped robots
IEEE Transactions on Robotics
Automated antenna design using paralleled differential evolution algorithm
International Journal of Computer Applications in Technology
Generation of neural networks using a genetic algorithm approach
International Journal of Bio-Inspired Computation
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This work presents the analysis of species evolution properties which are considered to design a new evolutionary algorithm for evolvable hardware. These properties reduce the risk of malfunctions in a physical system when it is evolving. A mathematical model, that characterises the natural evolution phenomena of a species, is proposed. A new evolutionary algorithm based on this model is proposed as well. This algorithm is designed to evolve hardware, e.g., to obtain the optimal control parameters of a real control system, while it is executing a repetitive task. The convergence of the proposed algorithm was proven by means of new theorems. Simulations and experimentation studies were carried out in order to validate the theoretical aspects and to evaluate the performance of the evolutionary algorithm.