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Evolving choice structures for genetic programming

Shuaiqiang Wang, Jun Ma, Jiming Liu, Xiaofei Niu
2010 Information Processing Letters  
It is quite difficult but essential for Genetic Programming (GP) to evolve the choice structures. Traditional approaches usually ignore this issue.  ...  Theoretical analysis and experiment results show that our method can evolve the programs with choice structures effectively within an acceptable additional time.  ...  Acknowledgements The authors would like to thank the editors and reviewers for their helpful comments. This research is supported by the Natural Science  ... 
doi:10.1016/j.ipl.2010.07.014 fatcat:27j2qo3d3ncefnq5lhscf37dpe

Automatic python programming using stack-based genetic programming

Hyun soo Park, Kyung Joong Kim
2012 Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12  
Traditional genetic programming uses tree-like data structure to represent a program.  ...  In this research, we propose to evolve bytecode of Python programming language by stack-based genetic programming.  ...  The initial work on evolving computer program is based on the RISC machine code with the genetic programming [1] . Since 1998, there have been several works on evolving JAVA bytecode.  ... 
doi:10.1145/2330784.2330899 dblp:conf/gecco/ParkK12 fatcat:cpx66rdwrfhshaj2lndwylwfau

Flexible Probabilistic Modeling for Search Based Test Data Generation

Robert Feldt, Shin Yoo
2020 Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops  
In particular, Probabilistic Programming languages (PPLs) and Genetic Programming (GP) should be investigated since they allow for very flexible probabilistic modelling.  ...  Such generative models can naturally be decomposed into a structured generator and a probabilistic model that determines how to make non-deterministic choices during generation.  ...  We also briefly discuss how Genetic Programming could be used to directly evolve also the code describing the structure of the data itself and not only its probabilistic model.  ... 
doi:10.1145/3387940.3392215 dblp:conf/icse/FeldtY20 fatcat:4xdujt2gy5budmkqh4bykkcejm

Using Multi-Objective Genetic Programming to Synthesize Stochastic Processes [chapter]

Brian Ross, Janine Imada
2009 Genetic Programming Theory and Practice VII  
We use genetic programming to automatically evolve a set of stochastic π-calculus expressions that generate execution behaviour conforming to some supplied target behaviour.  ...  KEY WORDS Genetic programming, process algebra, dynamic systems. † To be presented at Computational Intelligence 2007,  ...  Acknowledgment: Thanks to Janine Imada for helpful comments. Supported by NSERC Operating Grant 138467.  ... 
doi:10.1007/978-1-4419-1626-6_10 fatcat:vupm2r4tnna2refhsxlkvtr72e

Behavior Evolution of Autonomous Mobile Robot(AMR) using Genetic Programming Based on Evolvable Hardware

Kwee-Bo Sim, Dong-Wook Lee, Byoung-Tak Zhang
2002 International Journal of Fuzzy Logic and Intelligent Systems  
Genetic programming can be useful control method for evolvable hardware for its unique tree structured chromosome.  ...  This paper presents a genetic programming based evolutionary strategy for on-line adaptive learnable evolvable hardware.  ...  Introduction This paper present a method for evolving genetic programs on evolvable hardware.  ... 
doi:10.5391/ijfis.2002.2.1.020 fatcat:gqsklhd3crhhxjvg4hipnesqze

A case study where biology inspired a solution to a computer science problem

J R Koza, D Andre
1996 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
The out-of-sample error rate for the best genetically-evolved program achieved was slightly better than that of previously-reported human-written algorithms for this problem.  ...  Six new architecture-altering operations for genetic programming were motivated by the way that new biological structures, functions, and behaviors arise in nature using gene duplication.  ...  When automatically defined functions are being evolved in a run of genetic programming, it becomes necessary to determine the architecture of the overall tobe-evolved program.  ... 
pmid:9390254 fatcat:2p453gcebjgubkocqmhqobq5m4

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.  ...  This methodology involves creation of a database coding for known neuroanatomical and physiological constraints, for mental programs made of primitive cognitive functions, and for typical experiments with  ...  Instead of acting on digital chromosomes, as do genetic algorithms, genetic programming evolves entire computer programs.  ... 
doi:10.1024/1421-0185.64.4.231 fatcat:2ovdavn3tfbe5k7okxhcfgi2vy

Evolving Objects: A General Purpose Evolutionary Computation Library [chapter]

M. Keijzer, J. J. Merelo, G. Romero, Marc Schoenauer
2002 Lecture Notes in Computer Science  
This paper presents the evolving objects library (EOlib), an object-oriented framework for evolutionary computation (EC) that aims to provide a flexible set of classes to build EC applications.  ...  EOlib design objective is to be able to evolve any object in which fitness makes sense.  ...  Data Structures Any data structure can be evolved, if at least one variation operator is provided for such structures.  ... 
doi:10.1007/3-540-46033-0_19 fatcat:v54zwvtow5ei5fahdcbgwku73a

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

W. B. Langdon
1998 Genetic Programming and Data Structures  
Genetic Programming applies GAs to a "population" of programs -typically encoded as tree-structures.  ...  Genetic Programming uses novel optimisation techniques to "evolve" simple programs; mimicking the way humans construct programs by progressively re-writing them.  ...  Stack Based GP In most genetic programming work the programs being evolved use a prefix tree structured syntax. For the most part the LISP language is used.  ... 
doi:10.1007/978-1-4615-5731-9_2 fatcat:6tf27mxt55fn7jrn3sghhisbda

Evolving Bin Packing Heuristics with Genetic Programming [chapter]

E. K. Burke, M. R. Hyde, G. Kendall
2006 Lecture Notes in Computer Science  
This paper outlines a genetic programming system which evolves a heuristic that decides whether to put a piece in a bin when presented with the sum of the pieces already in the bin and the size of the  ...  Thus, the contribution of this paper is to demonstrate that genetic programming can be employed to automatically evolve bin packing heuristics which are the same as high quality heuristics which have been  ...  Genetic Programming Genetic programming [3] evolves a population of computer programs which are represented as tree structures.  ... 
doi:10.1007/11844297_87 fatcat:ummcjfd3tfgtdgwu5kfw2t4spq

Automated re-invention of six patented optical lens systems using genetic programming

John R. Koza, Sameer H. Al-Sakran, Lee W. Jones
2005 Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05  
The genetically evolved designs are instances of humancompetitive results produced by genetic programming in the field of optical design.  ...  This paper describes how genetic programming was used as an invention machine to automatically synthesize complete designs for six optical lens systems that duplicated the functionality of previously patented  ...  Choices of glass are typically drawn from a standard glass catalog. This paper describes how genetic programming can be used to automatically create a complete design for an optical lens system.  ... 
doi:10.1145/1068009.1068337 dblp:conf/gecco/KozaAJ05 fatcat:y5k2drewwnchpfy4lpmkclofzq

Automated synthesis of a human-competitive solution to the challenge problem of the 2002 international optical design conference by means of genetic programming and a multi-dimensional mutation operation

Lee W. Jones, Sameer H. Al-Sakran, John R. Koza
2006 Proceedings of the 8th annual conference on Genetic and evolutionary computation - GECCO '06  
by genetic programming.  ...  Second, this paper presents a mutation operation for numerical constants that is especially appropriate for problems in which the to-be-designed structure contains a large number of non-linearly interrelated  ...  Therefore, we claim that the genetically evolved result in this paper is an instance of "human-competitive" result produced by genetic programming.  ... 
doi:10.1145/1143997.1144143 dblp:conf/gecco/JonesAK06 fatcat:f7fhhnkzercebadkowoay2dlhq

Towards Practical Autoconstructive Evolution: Self-Evolution of Problem-Solving Genetic Programming Systems [chapter]

Lee Spector
2010 Genetic Programming Theory and Practice VIII  
Attempts to bring choices about operators and parameters under evolutionary control, through self-adaptative algorithms or meta-genetic programming, have been explored in the literature and have produced  ...  This chapter explores the prospects for extending the practical power of genetic programming through the refinement of an approach called autoconstructive evolution, in which the algorithms used for the  ...  Thanks also to the GPTP reviewers, to William Josiah Erikson for superb technical support, and to Hampshire College for support for the Hampshire College Institute for Computational Intelligence.  ... 
doi:10.1007/978-1-4419-7747-2_2 fatcat:23hiyjqhxvhbbf232nhils6say

Application of a Genetic Programming Based Rule Discovery System to Recurring Miscarriage Data [chapter]

Christian Setzkorn, Ray C. Paton, Leanne Bricker, Roy G. Farquharson
2000 Lecture Notes in Computer Science  
This paper introduces a rule inference system based on the paradigm of genetic programming. Rules are deduced from a medical data set related to recurring miscarriage.  ...  Freitas for his support during the development of this approach.  ...  Fig. 1 . 1 Structure of a genetic algorithm. Fig. 2 . 2 Example of genetic operation mutation for genetic programming.  ... 
doi:10.1007/3-540-39949-6_31 fatcat:lbxt5bpue5cvnn43l3fsoh2oga

Grammatical evolution: Evolving programs for an arbitrary language [chapter]

Conor Ryan, JJ Collins, Michael O Neill
1998 Lecture Notes in Computer Science  
We describe a Genetic Algorithm that can evolve complete programs.  ...  Using a variable length linear genome to govern how a Backus Naur Form grammar de nition is mapped to a program, expressions and programs of arbitrary complexity may be evolved.  ...  Hence, the structures being evolved can directly be evaluated.  ... 
doi:10.1007/bfb0055930 fatcat:q4lda5a75fbtbgrpbywxgmarxq
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