Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Principles in the Evolutionary Design of Digital Circuits—Part I
Genetic Programming and Evolvable Machines
Proceedings of the European Conference on Genetic Programming
Sub-machine-code GP: New Results and Extensions
Proceedings of the Second European Workshop on Genetic Programming
Floating Point Division and Square Root Algorithms and Implementation in the AMD-K7 Microprocessor
ARITH '99 Proceedings of the 14th IEEE Symposium on Computer Arithmetic
Evolutionary Design of Digital Circuits: Where Are Current Limits?
AHS '06 Proceedings of the first NASA/ESA conference on Adaptive Hardware and Systems
Redundancy and computational efficiency in Cartesian genetic programming
IEEE Transactions on Evolutionary Computation
Generalized Disjunction Decomposition for Evolvable Hardware
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A modified Karnaugh map technique
IEEE Transactions on Education
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Evolutionary algorithms can be used to evolve novel digital circuit solutions. This paper proposes the use of flexible target truth tables, allowing evolution more freedom where values are undefined. This concept is applied to three test circuits with different distributions of "don't care" values. Two strategies are introduced for utilising the undefined output values within the evolutionary algorithm. The use of flexible desired truth tables is shown to significantly improve the success of the algorithm in evolving circuits to perform this function. In addition, we show that this flexibility allows evolution to develop more hardware efficient solutions than using a fully-defined truth table.