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
Building Better Test Functions
Proceedings of the 6th International Conference on Genetic Algorithms
A Field Guide to Genetic Programming
A Field Guide to Genetic Programming
Using a Meta-GA for parametric optimization of simple gas in the computational chemistry domain
Proceedings of the 12th annual conference on Genetic and evolutionary computation
On the Emergence of Novel Behaviours From Complex Non Linear Systems
Proceedings of the 2010 conference on Biologically Inspired Cognitive Architectures 2010: Proceedings of the First Annual Meeting of the BICA Society
Automatically composing and parameterizing skills by evolving Finite State Automata
Robotics and Autonomous Systems
An ensemble of SVM classifiers based on gene pairs
Computers in Biology and Medicine
Taming parallel I/O complexity with auto-tuning
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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Pyevolve is an open-source framework for genetic algorithms. The initial long-term goal of the project was to create a complete and multi-platform framework for genetic algorithms in pure Python. However, the most recent developmental versions currently support also Genetic Programming (GP)[3]; accordingly, Pyevolve now aims at becoming a pure Python framework for evolutionary algorithms.