A Scalable Approach to Evolvable Hardware
Genetic Programming and Evolvable Machines
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Two-Step Incremental Evolution of a Prosthetic Hand Controller Based on Digital Logic Gates
ICES '01 Proceedings of the 4th International Conference on Evolvable Systems: From Biology to Hardware
Possibilities and Limitations of Applying Evolvable Hardware to Real-World Applications
FPL '00 Proceedings of the The Roadmap to Reconfigurable Computing, 10th International Workshop on Field-Programmable Logic and Applications
Incremental evolution of a signal classification hardware architecture for prosthetic hand control
International Journal of Knowledge-based and Intelligent Engineering Systems - Adaptive Hardwarel / Evolvable Hardware
An Online EHW Pattern Recognition System Applied to Face Image Recognition
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Challenges of evolvable hardware: past, present and the path to a promising future
Genetic Programming and Evolvable Machines
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Evolvable Hardware (EHW) has the potential to become new target hardware for complex real-world applications. However, several problems would have to be solved to make it widely applicable. This includes the difficulties in evolving large systems and the lack of generalization of gate level EHW. This paper proposes new methods targeting these problems, where evolving smaller sub-systems evolves a system. The experiments are based on a simplified image recognition task to be used in a roadway departure prevention system and later in an autonomous driving system. Special concern has been given to improve the generalization of the system. Experiments show that the number of generations required for evolution by the new method can be substantially reduced compared to evolving a system directly. This is with no reduction of the performance in the final system. Improvement in the generalization is shown as well.