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Introducing a Perl Genetic Programming System - and Can Meta-evolution Solve the Bloat Problem?
[chapter]
2003
Lecture Notes in Computer Science
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The supplied algorithm is strongly typed tree-based GP with homologous crossover. ...
The effect of per-node, fixed and self-adapting crossover and mutation rates on code growth and fitness is studied. ...
Macromutation is a little more complex. ...
doi:10.1007/3-540-36599-0_34
fatcat:dgmcunkgvfcelonan2fmlcsfra
A Rigorous Evaluation of Crossover and Mutation in Genetic Programming
[chapter]
2009
Lecture Notes in Computer Science
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We find that crossover does not significantly outperform mutation on most of the problems examined. ...
The role of crossover and mutation in Genetic Programming (GP) has been the subject of much debate since the emergence of the field. ...
Angeline [3] compared crossover to macromutation, arguing that the crossover operator may in fact function as a mutation operator of sorts. ...
doi:10.1007/978-3-642-01181-8_19
fatcat:dhpfuf4xafe7rjxmnpukgazhhu
Multi-task code reuse in genetic programming
2008
Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08
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The technical means of code reuse is a crossbreeding operator which works very similar to standard tree-swapping crossover. ...
The population contains 500 individuals and evolves for 200 generations using crossover with probability 0.9 and mutation (substituting subtree with a new random one) with probability 0.1. ...
From the internal perspective of an evolutionary run that solves A, crossbreeding is a mutation (macromutation) operator, as it replaces a subtree in an individual in A by another subtree; the only difference ...
doi:10.1145/1388969.1389040
dblp:conf/gecco/JaskowskiKW08a
fatcat:ickxeofvkzgrxp2xj7vwodkkfq
Instruction-Matrix-Based Genetic Programming
2008
IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
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The testing errors are also comparable to or better than those obtained with well-known classifiers. ...
IMGP maintains an IM to evolve tree nodes and subtrees separately. IMGP extracts program trees from an IM and updates the IM with the information of the extracted program trees. ...
The crossover is similar to context-preserving crossover [10] because the two subtrees of the parents must be in the same position to reduce the macromutation effect of the standard crossover [1] . ...
doi:10.1109/tsmcb.2008.922054
pmid:18632395
fatcat:refyzh5nx5efzgsms3abbrjmmi
Opposites Attract: Complementary Phenotype Selection for Crossover in Genetic Programming
[chapter]
2002
Lecture Notes in Computer Science
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His conclusion is that crossover plays the functional role of "macromutation" rather than "building block engine," as in GAs. ...
Standard crossover in genetic programming (GP) selects two parents independently, based on fitness, and swaps randomly chosen portions of genetic material (subtrees). ...
Following [12] , in each parent we randomly select an internal node with 90% probability or a leaf node with 10% probability, and swap the subtrees rooted in these nodes. ...
doi:10.1007/3-540-45712-7_14
fatcat:uq67lggnbndlbo7xanb5male3q
Bloat Control Operators and Diversity in Genetic Programming: A Comparative Study
2010
Evolutionary Computation
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This comparison study can provide the practitioner with some relevant clues as to which bloat control method is better suited to a particular problem and whether the advantage of a method does or does ...
The aim of the work was to demonstrate that macromutation could perform as well as subtree crossover under identical experimental conditions. ...
The hitchhiking theory is proposed by Tackett (1994) , who proved that random selection in conjunction with standard subtree crossover (i.e., when fitness is completely ignored) does not cause code growth ...
doi:10.1162/evco.2010.18.2.18206
pmid:20210598
fatcat:27m6pnrkdbgabmqwdkvza3bncu
Evolving controllers for simulated car racing using object oriented genetic programming
2007
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07
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Several different controller representations are compared on a non-trivial problem in simulated car racing, with respect to learning speed and final fitness. ...
These are Subtree macro-mutation (MM -substituting a node in the tree with an entirely randomly generated subtree of the same return type, under depth or size contraints), and homologous Uniform Crossover ...
In this paper we are therefore comparing this representation with larger feed-forward neural networks, recurrent networks, and several types of GP. ...
doi:10.1145/1276958.1277271
dblp:conf/gecco/AgapitosTL07
fatcat:eku4lglf5fh4tpldvmtmhskgmu
Multiobjective Evolutionary Search of Difference Equations-based Models for Understanding Chaotic Systems
[chapter]
2008
Foundations of Generic Optimization
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Unless we include in the objective function some terms that depend on the properties on the reconstructed attractor, we may end up with a non chaotic model. ...
In previous works [42] , we have proposed to implement the macromutation in the SA algorithm by means of a subtree crossover with a randomly generated individual [21, 37] . ...
Each node of this tree will encode the name of the production rule that originated each subtree. This information will be used later to define a typed crossover. ...
doi:10.1007/978-1-4020-6668-9_4
fatcat:lragipoprbgqjbjafvgropq6uu
Fitness distributions in evolutionary computation: motivation and examples in the continuous domain
1999
Biosystems (Amsterdam. Print)
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Subtree Crossover: Building Block En- Forms of Crossover in Evolutionary Computation on Lin-
gine or Macromutation? Genetic Programming 1997. Pro- ear Systems of Equations. ...
A preliminary investigation into evolving
sions derived from comparing different variation modular programs without subtree crossover. ...
doi:10.1016/s0303-2647(99)00057-x
pmid:10658834
fatcat:a5yxosxan5hrdebvyaedjlpwky
Using Symbolic Regression to Infer Strategies from Experimental Data
[chapter]
2002
Studies in Fuzziness and Soft Computing
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It then cuts the two subtrees at these nodes, swaps them and recombines the subtrees with the parent trees. ...
itself serves as a kind of macromutation. ...
doi:10.1007/978-3-7908-1784-3_4
fatcat:njchsy3clvecviuzdy5qurkscu
Neutral Variations Cause Bloat in Linear GP
[chapter]
2003
Lecture Notes in Computer Science
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A mutation-based variant of linear GP is applied that operates with minimum structural step sizes. ...
The potential destruction caused by removing a subtree depends on the subtree size. The effect of the replacing subtree on the fitness, instead, is independent from its size. ...
Contrary to this, the performance never drops in the nononeff experiment (compared to the baseline result). ...
doi:10.1007/3-540-36599-0_26
fatcat:jki7h4jlzzf2tfecej7x3txlia
Using genetic programming for the induction of novice procedural programming solution algorithms
2002
Proceedings of the 2002 ACM symposium on Applied computing - SAC '02
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However, the large-scale use of intelligent programming tutors has been impeded by the high developmental costs associated with building intelligent programming tutors. ...
The crossover operator implemented by Langdon [LANG94] selects a subtree in one individual and replaces it with a randomly selected subtree from another individual. ...
[BANZ98] and Angeline [ANGE97] describe the macromutation operator, also known as "headless chicken crossover", as a possible improvement over the standard crossover operator. ...
doi:10.1145/508895.508903
fatcat:4djzv5q6brhexojtygzxvaoeri
The molecule evoluator
2005
Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05
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Additionally, we use interaction with the user as a fitness function, which is new in evolutionary algorithms in drug design. ...
CROSSOVER AND MUTATION Crossover is implemented like crossover in standard genetic programming [2] : subtrees of two different molecules are selected and swapped. ...
crossover. ...
doi:10.1145/1068009.1068339
dblp:conf/gecco/LameijerIK05
fatcat:gk2q7g6azzc2vpwbhx3rkdvk2y
A review on the application of evolutionary computation to information retrieval
2003
International Journal of Approximate Reasoning
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It is composed of a roulette-wheel selection, an usual GP crossover and a mutation operator based on swapping subtrees. ...
approach and with a dimensionality and updating speed comparable to those of the existing indexing techniques. ...
doi:10.1016/j.ijar.2003.07.010
fatcat:iyccqeqltnbbzcul5aggjbnehm
A new evolutionary algorithm combining simulated annealing and genetic programming for relevance feedback in fuzzy information retrieval systems
2002
Soft Computing - A Fusion of Foundations, Methodologies and Applications
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The performance of the proposed technique will be compared with the only previous existing approach to perform this task, Kraft et al.' ...
Genetic operators: The usual GP crossover is considered [21] , which is based on randomly selecting one edge in each parent and exchanging both subtrees from these edges between the both parents. ...
Apart from adapting the crossover and mutation operators to deal with the specific coding scheme considered, the remaining algorithm components remain the same. ...
doi:10.1007/s00500-002-0184-8
fatcat:fc3l2hxqajbanhbjyuo3qdosni
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