Online Program Simplification in Genetic Programming

Zhang, Mengjie; Wong, Phillip; Qian, Dongping

doi:10.1007/11903697_75

Cited by 22 publications

(20 citation statements)

References 5 publications

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“…(Complete data can be found in [23] from which a less clear trend emerges: mostly, test error is unchanged, sometimes it improves, sometimes it degrades.) This picture of unclear effects on test error has also been reported in [30,31]. Training the GP trees with 100 data but retaining a validation set size (that was used for pruning) of 20 data, however, does produce a consistent pattern.…”

Section: Effect Of Pruning On the Generalization Errorsupporting

confidence: 56%

“…It is therefore desirable to remove as much of this redundant material as possible. Although manual tree simplification has been used in the past [14], automated tree simplification is much preferred but is very challenging [31]; Naoki et al [18] point out that canonical simplification is not Turing computable. Work on the simplification of GP trees has been reviewed by Kinzett et al [13].…”

mentioning

confidence: 99%

“…Zhang and co-workers [30,31] have explored the use of hashing to simplify trees both at the end of a run as well as during the evolutionary run. These authors found, unsurprisingly, that simplification reduced tree sizes although the effect on test performance was not examined with any formal statistical procedure and does appear to have been resolved.…”

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confidence: 99%

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Pruning of genetic programming trees using permutation tests

Rockett

2020

Evol. Intel.

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We present a novel approach based on statistical permutation tests for pruning redundant subtrees from genetic programming (GP) trees that allows us to explore the extent of effective redundancy. We observe that over a range of regression problems, median tree sizes are reduced by around 20% largely independent of test function, and that while some large subtrees are removed, the median pruned subtree comprises just three nodes; most take the form of an exact algebraic simplification. Our statistically-based pruning technique has allowed us to explore the hypothesis that a given subtree can be replaced with a constant if this substitution results in no statistical change to the behavior of the parent tree-what we term approximate simplification. In the eventuality, we infer that more than 95% of the accepted pruning proposals are the result of algebraic simplifications, which provides some practical insight into the scope of removing redundancies in GP trees.

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Section: Effect Of Pruning On the Generalization Errorsupporting

confidence: 56%

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confidence: 99%

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Pruning of genetic programming trees using permutation tests

Rockett

2020

Evol. Intel.

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“…In order to reduce the program sizes and to speed up the evolution, we need to apply simplification during the evolution. Although this approach has been studied in the past [6], its impact on PushGP is still unknown.…”

Section: Introductionmentioning

confidence: 99%

A quantitative analysis of the simplification genetic operator

Zhan

2014

Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

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The simplification function was introduced to PushGP as a tool to reduce the sizes of evolved programs in final reports. While previous work suggests that simplification could reduce the sizes significantly, nothing has been done to study its impacts on the evolution of Push programs. In this paper, we show the impact of simplification as a genetic operator. By conducting test runs on the U.S. change problem, we show that using simplification operator with PushGP, lexicase selection and ULTRA could increase the possibility to find solutions in the short term while it might remove some useful genetic materials for the long term.

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“…However, bloating also hampers the algorithm's work by increasing the expression length and therefore the time required to compute them, and also by leading the algorithm along the blind alley. It can be resolved with the online simplification [Zhang et al, 2006], [Kinzett et al, 2008], when all expressions in the pool are simplified with some frequency. There exist other approaches ( [Poli et al, 2008], [Mori et al, 2009]), however online simplification is considered to be more effective.…”

Section: Introductionmentioning

confidence: 99%

Internal and Online Simplification in Genetic Programming: an Experimental Comparison

Borcheninov¹,

Okulovsky²

2012

Proceedings of the Spring/Summer Young Researchers' Colloquium on Software Engineering

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Abstract-Genetic programming is an evolutionary algorithm, which allows performing symbolic regression -the important task of obtaining the analytical form of a model by the data, produced by the model. One of the known problems of genetic programming is expressions' bloating that results in ineffictevely long expressions. To prevent bloating, symbolic simplification of expression is used. We introduce a new approach to simplification in genetic programming, making it a uniform part of the evolutionary process. To do that, we develop a genetic programming on the basis of transofmation rules, similarly to computer algebra systems. We compare our approach with existed solution, and prove its adequacy and effectiviness.

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Online Program Simplification in Genetic Programming

Cited by 22 publications

References 5 publications

Pruning of genetic programming trees using permutation tests

Pruning of genetic programming trees using permutation tests

A quantitative analysis of the simplification genetic operator

Internal and Online Simplification in Genetic Programming: an Experimental Comparison

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