Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
A Fitness Estimation Strategy for Genetic Algorithms
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
LOCO-I: a low complexity, context-based, lossless image compression algorithm
DCC '96 Proceedings of the Conference on Data Compression
On-Line Compression of High Precision Printer Images by Evolvable Hardware
DCC '98 Proceedings of the Conference on Data Compression
The Fast Evaluation Strategy for Evolvable Hardware
Genetic Programming and Evolvable Machines
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A hardware implementation of an evolutionary algorithm is capable of running much faster than a software implementation. However, the speed advantage of the hardware implementation will disappear for slow fitness evaluation systems. In this paper a Fast Evolutionary Algorithm (FEA) is implemented in hardware to examine the real time advantage of such a system. The timing specifications show that the hardware FEA is approximately 50 times faster than the software FEA. An image compression hardware subsystem is used as the fitness evaluation unit for the hardware FEA to show the benefit of the FEA for time-consuming applications in a hardware environment. The results show that the FEA is faster than the EA and generates better compression ratios.