Journal of Electronic Testing: Theory and Applications
Feedback-based coverage directed test generation: an industrial evaluation
HVC'10 Proceedings of the 6th international conference on Hardware and software: verification and testing
Evolutionary failing-test generation for modern microprocessors
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Bayesian network structure learning from limited datasets through graph evolution
EuroGP'12 Proceedings of the 15th European conference on Genetic Programming
An evolutionary approach to wetlands design
EvoBIO'13 Proceedings of the 11th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
An evolutionary framework for routing protocol analysis in wireless sensor networks
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
A memetic approach to bayesian network structure learning
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
An efficient distance metric for linear genetic programming
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Evolutionary optimization of wetlands design
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled GP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers.For a practitioner, GP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.For an evolutionary computation researcher, GP may be regarded as a platform where new operators and strategies can be easily tested.