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
Genetic programming in C++: implementation issues
Advances in genetic programming
Evolving Turing-Complete Programs for a Register Machine with Self-modifying Code
Proceedings of the 6th International Conference on Genetic Algorithms
Parallel Genetic Programming on a Network of Transputers
Parallel Genetic Programming on a Network of Transputers
Starting FORTH
Genetic Programming and Autoconstructive Evolution with the Push Programming Language
Genetic Programming and Evolvable Machines
An Adaptive Mapping for Developmental Genetic Programming
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Sub-machine-code GP: New Results and Extensions
Proceedings of the Second European Workshop on Genetic Programming
VECPAR '00 Selected Papers and Invited Talks from the 4th International Conference on Vector and Parallel Processing
Modification point depth and genome growth in genetic programming
Evolutionary Computation
The Push3 execution stack and the evolution of control
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetic parallel programming: design and implementation
Evolutionary Computation
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Information Sciences: an International Journal
Compressed linear genetic programming: empirical parameter study on the Even-n-parity problem
EC'05 Proceedings of the 6th WSEAS international conference on Evolutionary computing
Improved approach of genetic programming and applications for data mining
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Teams of genetic predictors for inverse problem solving
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
| Hi-index | 0.00 |
HiGP is a new high-performance genetic programming system. This system combines techniques from string-based genetic algorithms, S-expression-based genetic programming systems, and high-performance parallel computing. The result is a fast, flexible, and easily portable genetic programming engine with a clear and efficient parallel implementation. HiGP manipulates and produces linear programs for a stack-based virtual machine, rather than the tree-structured S-expressions used in traditional genetic programming. In this paper we describe the HiGP virtual machine and genetic programming algorithms. We demonstrate the system's performance on a symbolic regression problem and show that HiGP can solve this problem with substantially less computational effort than can a traditional genetic programming system. We also show that HiGP's time performance is significantly better than that of a well-written S-expression-based system, also written in C. We further show that our parallel version of HiGP achieves a speedup that is nearly linear in the number of processors, without mandating the use of localized breeding strategies.