Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low power electronics and design
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Papers from an international workshop on Towards Evolvable Hardware, The Evolutionary Engineering Approach
Scalability Problems of Digital Circuit Evolution: Evolvability and Efficient Designs
EH '00 Proceedings of the 2nd NASA/DoD workshop on Evolvable Hardware
Toward Evolvable Hardware Chips: Experiments with a Programmable Transistor Array
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Evolvable hardware: using evolutionary computation to design and optimize hardware systems
IEEE Computational Intelligence Magazine
Promises and challenges of evolvable hardware
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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EHW is the acronym used to denote an emerging and relatively new research field in digital hardware design; it stands for Evolvable Hardware. This technique has attracted many researchers since the 1990's. EHW aims at an automatic design and optimisation of a reconfigurable hardware system using Evolutionary Algorithms (EAs), such as Genetic Algorithms, Genetic programming etc. This article is published as part of a three years research project. The objective of this project is to employ the above method on a target specific hardware, the Embryonics Hardware System. The latter requires large hardware resources. Thus, in this project, EAs will be used to evolve the Embryonics Hardware System to discover novel design with reduced complexity. The new design must first ensure the correct functionality. Hence to verify the concept of Evolvable Hardware, the authors, in this paper, focus on the design of relatively simple combinatorial logic circuits using Genetic Algorithms with multi-objective fitness.