An adaptive crossover distribution mechanism for genetic algorithms
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
The ARGOT strategy: adaptive representation genetic optimizer technique
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
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
Evolving programmers: the co-evolution of intelligent recombination operators
Advances in genetic programming
Extending genetic programming with recombinative guidance
Advances in genetic programming
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
SAW-ing EAs: adapting the fitness function for solving constrained problems
New ideas in optimization
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Principles in the Evolutionary Design of Digital Circuits—Part I
Genetic Programming and Evolvable Machines
Genetic Programming and Evolvable Machines
Genetic Programming and Autoconstructive Evolution with the Push Programming Language
Genetic Programming and Evolvable Machines
Adapting Operator Probabilities in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Adaptively Resizing Populations: An Algorithm and Analysis
Proceedings of the 5th International Conference on Genetic Algorithms
Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Genetic Programming with Adaptive Representations
Genetic Programming with Adaptive Representations
The behavior of adaptive systems which employ genetic and correlation algorithms
The behavior of adaptive systems which employ genetic and correlation algorithms
Adaptive representation for single objective optimization
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Evolving Evolutionary Algorithms with Patterns
Soft Computing - A Fusion of Foundations, Methodologies and Applications
A-Brain: a general system for solving data analysis problems
Journal of Experimental & Theoretical Artificial Intelligence
Exploiting auto-adaptive µGP for highly effective test programs generation
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Parameter control in evolutionary algorithms
IEEE Transactions on Evolutionary Computation
A comparison of linear genetic programming and neural networks inmedical data mining
IEEE Transactions on Evolutionary Computation
An Adaptive GP Strategy for Evolving Digital Circuits
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Two layered Genetic Programming for mixed-attribute data classification
Applied Soft Computing
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part I
Lazy learning for multi-class classification using genetic programming
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
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The aim of this research is to develop an autonomous system for solving data analysis problems. The system, called Genetic Programming-Autonomous Solver (GP-AS) contains most of the features required by an autonomous software: it decides if it knows or not how to solve a particular problem, it can construct solutions for new problems, it can store the created solutions for later use, it can improve the existing solutions in the idle-time it can efficiently manage the computer resources for fast running speed and it can detect and handle failure cases. The generator of solutions for new problems is based on an adaptive variant of Genetic Programming. We have tested this part by solving some well-known problems in the field of symbolic regression and classification. Numerical experiments show that the GP-AS system is able to perform very well on the considered test problems being able to successfully compete with standard GP having manually set parameters.