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Automated Problem Decomposition for the Boolean Domain with Genetic Programming [chapter]

Fernando E. B. Otero, Colin G. Johnson
2013 Lecture Notes in Computer Science  
Most previous works on modularity in GP emphasise the structure of modules used to encapsulate code and/or promote code reuse, instead of in the decomposition of the original problem.  ...  Researchers have been interested in exploring the regularities and modularity of the problem space in genetic programming (GP) with the aim of decomposing the original problem into several smaller subproblems  ...  In ADFs, the structure of program trees is defined in a way that subtrees with different roles are evolved in parallele.g., there are function-defining subtrees and a result-producing subtree, which can  ... 
doi:10.1007/978-3-642-37207-0_15 fatcat:n3bb6zbgung2rg64laztmehajy

Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design

Gregory S. Hornby
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
Here we claim that these characteristics are enabled by implementing the attributes of combination, control-flow and abstraction in the representation.  ...  To support this claim we use an evolutionary algorithm to evolve solutions to different sizes of a table design problem using five different representations, each with different combinations of modularity  ...  Hierarchy is the number of layers of encapsulated modules in the structure of a design.  ... 
doi:10.1145/1068009.1068297 dblp:conf/gecco/Hornby05 fatcat:varbnyeblncbrjuxzb4sbxim7m

Sequential Symbolic Regression with Genetic Programming [chapter]

Luiz Otávio V.B. Oliveira, Fernando E.B. Otero, Gisele L. Pappa, Julio Albinati
2015 Genetic and Evolutionary Computation  
The method was tested in eight polynomial functions, and compared with canonical genetic programming (GP) and geometric semantic genetic programming (SGP).  ...  The rationale behind SSR is that, after generating a suboptimal function f via symbolic regression, the output errors can be approximated by another function in a subsequent iteration.  ...  Geometric Semantic Operators Standard genetic programming operators were originally conceived to operate in the syntatic-level of the solutions being evolved.  ... 
doi:10.1007/978-3-319-16030-6_5 dblp:conf/gptp/OliveiraOPA14 fatcat:fko7mhdpejbsll3ana5yixfzbu

Reuse, parameterized reuse, and hierarchical reuse of substructures in evolving electrical circuits using genetic programming [chapter]

John R. Koza, Forrest H. Bennett, David Andre, Martin A. Keane
1997 Lecture Notes in Computer Science  
In this paper, we successfully evolved a design for a twoband crossover (woofer and tweeter) filter with a crossover frequency of 2,512  ...  Genetic programming with automatically defined functions and the recently developed architecturealtering operations provides a way to build complex structures with reused substructures.  ...  Related Paper in this Volume See also in this volume.  ... 
doi:10.1007/3-540-63173-9_56 fatcat:4nac23icqvcqljmjmkulkukbju

Using genetic programming for the induction of novice procedural programming solution algorithms

Nelishia Pillay
2002 Proceedings of the 2002 ACM symposium on Applied computing - SAC '02  
In addition to this, the study has also identified a means of overcoming premature convergence caused by fitness function biases in a genetic programming system for the induction of novice procedural programming  ...  In this study the genetic programming system must be capable of solving a number of different programming problems in different application domains.  ...  A number of the solutions induced by the genetic programming system contained redundant code.  ... 
doi:10.1145/508895.508903 fatcat:4djzv5q6brhexojtygzxvaoeri

Genetic Programming — Computers Using "Natural Selection" to Generate Programs [chapter]

W. B. Langdon
1998 Genetic Programming and Data Structures  
Genetic Programming uses novel optimisation techniques to "evolve" simple programs; mimicking the way humans construct programs by progressively re-writing them.  ...  Next it introduces Genetic Programming, describing its history and describing the technique via a worked example in C.  ...  Module Acquisition The Genetic Library Builder (GLiB) [Ang94] implements encapsulation by adding a complementary pair of genetic operators, compression (encapsulation) and decompression which are applied  ... 
doi:10.1007/978-1-4615-5731-9_2 fatcat:6tf27mxt55fn7jrn3sghhisbda

Evolving High-Level Imperative Program Trees with Strongly Formed Genetic Programming [chapter]

Tom Castle, Colin G. Johnson
2012 Lecture Notes in Computer Science  
We present a set of extensions to Montana's popular Strongly Typed Genetic Programming system that introduce constraints on the structure of program trees.  ...  It is demonstrated that these constraints can be used to evolve programs with a naturally imperative structure, using common high-level imperative language constructs such as loops.  ...  Introduction Evolving high-level imperative programs with genetic programming (GP) [1] is challenging.  ... 
doi:10.1007/978-3-642-29139-5_1 fatcat:oeai5gjazrgr7pvesgm6r5hna4

Evaluating GP schema in context

Hammad Majeed, Conor Ryan, R. Muhammad Atif Azad
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
We propose a new methodology to look at the fitness contributions (semantics) of different schemata in Genetic Programming (GP).  ...  We hypothesize that the significance of a schema can be evaluated by calculating its fitness contribution to the total fitness of the trees that contain it, and use our methodology to test this hypothesis  ...  Iba and de Garis [2] also calculate the worth of the constituent subtrees of an individual by treating each subtree as an independent program.  ... 
doi:10.1145/1068009.1068304 dblp:conf/gecco/MajeedRA05 fatcat:nsyw5p36xnccrmqdikjh22sepy

Evolving Structure-Function Mappings in Cognitive Neuroscience Using Genetic Programming

Fernand Gobet, Amanda Parker
2005 Swiss Journal of Psychology  
using genetic programming A primary aim in science is to develop theories that summarize and unify a large body of experimental data.  ...  The evolutionary algorithms evolve theories mapping structures to functions in order to optimize the fit with the actual data. These theories lead to new, empirically testable predictions.  ...  This also enables the direct use of genetic-programming subtree-encapsulation methods (Koza, 1994) . hierarchically; (c) a one-to-one, one-to-many or a many-to-one mapping may link functions and structures  ... 
doi:10.1024/1421-0185.64.4.231 fatcat:2ovdavn3tfbe5k7okxhcfgi2vy

Applying Genetic Programming with Substructure Discovery to a Traffic Signal Control Problem
頻出部分木発見手法を用いた遺伝的プログラミングの交通信号制御問題への適用

Juncichi Kumagai, Yasuo Ojima, Souichi Takashige, Yoshitaka Kameya, Taisuke Sato
2007 Transactions of the Japanese society for artificial intelligence  
To build such an agent program automatically, we introduce genetic programming (GP), an evolutionary method for program construction.  ...  In GP, it is known as important to encapsulate the substructures of a program which leads to higher fitness to the environment, and we propose a new encapsulation method using an efficient technique for  ...  Koza, Evolving Modules in Genetic Programming by Subtree Encapsulation, Proc. of the 4th European Conf. on Genetic Programming, 2001. [Mikami 94] S. Mikami and Y.  ... 
doi:10.1527/tjsai.22.127 fatcat:ze576djwxrcbjkw7uqc6xllvaq

Model Generation Using Genetic Programming [chapter]

A. Salhi, H. Glaser, D. De Roure
1996 UK Parallel '96  
Automatically Defined Functions: In [?] ADF's have been extensively studied. They are evolvable modules of an evolving genetic programme.  ...  Genetic Programming: A Review Genetic Programming (GP) pioneered by J.Koza [?, ?, ?] , [?] . is an extension of GA's to operate over spaces whose elements are programmes.  ... 
doi:10.1007/978-1-4471-1504-5_7 dblp:conf/ppsg/SalhiGR96 fatcat:4zowzxirnzdjdowvir665alhc4

Context-aware mutation

Hammad Majeed, Conor Ryan
2007 Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07  
Context-Aware mutation operates by replacing existing sub-trees with modules from a previously constructed repository of possibly useful subtrees.  ...  This paper introduces a new type of mutation, Context-Aware Mutation, which is inspired by the recently introduced context-aware crossover.  ...  BACKGROUND The idea of modularization is not new in Genetic Programming and many efforts have been made in the past with varying degrees of success.  ... 
doi:10.1145/1276958.1277285 dblp:conf/gecco/MajeedR07 fatcat:zpcu6dxrdfdnjbudygwcui7aoq

Grammar Design for Derivation Tree Based Genetic Programming Systems [chapter]

Stefan Forstenlechner, Miguel Nicolau, David Fagan, Michael O'Neill
2016 Lecture Notes in Computer Science  
Grammar-based genetic programming systems have gained interest in recent decades and are widely used nowadays.  ...  The results show that the overall structure for derivation trees created by the grammar has little effect on the performance, but still affects the genetic material changed by search operators.  ...  This research is based upon works supported by the Science Foundation Ireland, under Grant No. 13/IA/1850. Grammar Design for Derivation Tree Based Genetic Programming Systems  ... 
doi:10.1007/978-3-319-30668-1_13 fatcat:gosnthngznay5mjhtwwte5gmde

Towards identifying salient patterns in genetic programming individuals

András Joó, Juan Pablo Neirotti
2009 Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09  
This thesis addresses the problem of offline identification of salient patterns in genetic programming individuals.  ...  into the course of evolution and (c) should be helpful in optimizing future runs.  ...  [70, 71] ) the first description of the usage of genetic programming in evolving learning rules is reported by Bengio et al. [72] .  ... 
doi:10.1145/1569901.1570217 dblp:conf/gecco/JooN09 fatcat:j4hjmnmeffgg3mrnmqxshuz5uq

Run Transferable Libraries — Learning Functional Bias in Problem Domains [chapter]

Maarten Keijzer, Conor Ryan, Mike Cattolico
2004 Lecture Notes in Computer Science  
This paper introduces the notion of Run Transferable Libraries, a mechanism to pass knowledge acquired in one GP run to another.  ...  We demonstrate that a system using these libraries can solve a selection of standard benchmarks considerably more quickly than GP with ADFs by building knowledge about a problem.  ...  Once a run is finished, all the effort involved in producing these modules must be repeated for the next run. A different approach was taken by [7] with their Subtree Encapsulation method.  ... 
doi:10.1007/978-3-540-24855-2_63 fatcat:o5sq6hoqm5fodd7txdytyfiesm
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