Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Principles in the Evolutionary Design of Digital Circuits—Part I
Genetic Programming and Evolvable Machines
Principles in the Evolutionary Design of Digital Circuits—Part II
Genetic Programming and Evolvable Machines
Towards the Automatic Design of More Efficient Digital Circuits
EH '00 Proceedings of the 2nd NASA/DoD workshop on Evolvable Hardware
Automated design and knowledge discovery of logic circuits using a multi-objective adaptive GA
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Promises and challenges of evolvable hardware
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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As an important branch of evolvable hardware, evolutionary design of circuit (EDC) is a promising way to realize automated design of complex electronic circuits. To improve EDC in efficiency, scalability and capability of optimization, a novel technique was developed. It features an adaptive multi-objective genetic algorithm and interactions between EDC and data mining. It was validated by the experiments on arithmetic circuits, showing some exciting results. Some circuits evolved are the best ones ever reported in terms of gate count and operating speed. Moreover, some novel knowledge, e.g., efficient and scalable design formulae and generalized transform rules have been discovered by mining the data and results of EDC, which are easy to verify but difficult to dig out by human experts with existing knowledge.