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 programming II: automatic discovery of reusable programs
Genetic programming II: automatic discovery of reusable programs
Discovery of subroutines in genetic programming
Advances in genetic programming
Principles in the Evolutionary Design of Digital Circuits—Part I
Genetic Programming and Evolvable Machines
A Scalable Approach to Evolvable Hardware
Genetic Programming and Evolvable Machines
Simultaneous Discovery of Reusable Detectors and Subroutines Using Genetic Programming
Proceedings of the 5th International Conference on Genetic Algorithms
Evolving Modules in Genetic Programming by Subtree Encapsulation
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
A Divide-and-Conquer Approach to Evolvable Hardware
ICES '98 Proceedings of the Second International Conference on Evolvable Systems: From Biology to Hardware
Layered learning in boolean GP problems
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Use of particle swarm optimization to design combinational logic circuits
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
Automated synthesis of analog electrical circuits by means ofgenetic programming
IEEE Transactions on Evolutionary Computation
Explorations in design space: unconventional electronics designthrough artificial evolution
IEEE Transactions on Evolutionary Computation
An evolutionary approach to automatic synthesis of high-performance analog integrated circuits
IEEE Transactions on Evolutionary Computation
A three-step decomposition method for the evolutionary design of sequential logic circuits
Genetic Programming and Evolvable Machines
Evolvable hardware design based on a novel simulated annealing in an embedded system
Concurrency and Computation: Practice & Experience
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In an effort to enable evolutionary computation techniques to discover solutions for large and complex hardware systems, techniques have been devised to break the initial problem down into smaller sub-tasks. In particular, a decomposition approach has been described that is based on partitioning of the circuit test vectors, but it has its limitations. In an effort to address this, we have combined the partitioning method with an incrementally evolving genetic programming approach. The result, referred to as Partitioned Incremental Evolution of HARDware (PIE-HARD), exhibits solution-finding performance that is significantly better than that of other approaches.