@inproceedings{1144154, added-at = {2008-06-19T17:46:40.000+0200}, address = {Seattle, Washington, USA}, author = {Walker, James Alfred and Miller, Julian Francis}, biburl = {http://www.bibsonomy.org/bibtex/2dae12a51b2b2388fee40ac9e2c311b61/brazovayeye}, booktitle = {{GECCO 2006:} Proceedings of the 8th annual conference on Genetic and evolutionary computation}, doi = {doi:10.1145/1143997.1144154}, editor = {Keijzer, Maarten and Cattolico, Mike and Arnold, Dirk and Babovic, Vladan and Blum, Christian and Bosman, Peter and Butz, Martin V. and {Coello Coello}, Carlos and Dasgupta, Dipankar and Ficici, Sevan G. and Foster, James and Hernandez-Aguirre, Arturo and Hornby, Greg and Lipson, Hod and McMinn, Phil and Moore, Jason and Raidl, Guenther and Rothlauf, Franz and Ryan, Conor and Thierens, Dirk}, interhash = {7ed90c1560381176f19dbcdee8f6df36}, intrahash = {dae12a51b2b2388fee40ac9e2c311b61}, isbn = {1-59593-186-4}, keywords = {Cartesian acquisition, algorithms, automatically defined embedded evolution, functions, genetic hierarchical-if-and-only-if, lawnmower module problem, program programming, synthesis synthesis,}, month = {8-12 July}, notes = {GECCO-2006 A joint meeting of the fifteenth international conference on genetic algorithms (ICGA-2006) and the eleventh annual genetic programming conference (GP-2006). ACM Order Number 910060}, organisation = {ACM SIGEVO (formerly ISGEC)}, pages = {911--918}, publisher = {ACM Press}, publisher_address = {New York, NY, 10286-1405, USA}, timestamp = {2008-06-19T17:46:40.000+0200}, title = {Embedded cartesian genetic programming and the lawnmower and hierarchical-if-and-only-if problems}, url = {http://www.cs.bham.ac.uk/~wbl/biblio/gecco2006/docs/p911.pdf}, volume = 1, year = 2006 } @inproceedings{1144153, added-at = {2008-06-19T17:46:40.000+0200}, address = {Seattle, Washington, USA}, author = {Walker, James Alfred and Miller, Julian Francis and Cavill, Rachel}, biburl = {http://www.bibsonomy.org/bibtex/24ef4b6004cc046b1d75259dacf702d87/brazovayeye}, booktitle = {{GECCO 2006:} Proceedings of the 8th annual conference on Genetic and evolutionary computation}, doi = {doi:10.1145/1143997.1144153}, editor = {Keijzer, Maarten and Cattolico, Mike and Arnold, Dirk and Babovic, Vladan and Blum, Christian and Bosman, Peter and Butz, Martin V. and {Coello Coello}, Carlos and Dasgupta, Dipankar and Ficici, Sevan G. and Foster, James and Hernandez-Aguirre, Arturo and Hornby, Greg and Lipson, Hod and McMinn, Phil and Moore, Jason and Raidl, Guenther and Rothlauf, Franz and Ryan, Conor and Thierens, Dirk}, interhash = {f16aafe72a80dedecb9e3d1b957c6f7f}, intrahash = {4ef4b6004cc046b1d75259dacf702d87}, isbn = {1-59593-186-4}, keywords = {Cartesian ES, acquisition, algorithms, automatically circuits, defined digital embedded evolution, evolutionary functions, genetic module multi-chromosome multi-chromosome, program programming, strategy, synthesis synthesis,}, month = {8-12 July}, notes = {GECCO-2006 A joint meeting of the fifteenth international conference on genetic algorithms (ICGA-2006) and the eleventh annual genetic programming conference (GP-2006). ACM Order Number 910060}, organisation = {ACM SIGEVO (formerly ISGEC)}, pages = {903--910}, publisher = {ACM Press}, publisher_address = {New York, NY, 10286-1405, USA}, timestamp = {2008-06-19T17:46:40.000+0200}, title = {A multi-chromosome approach to standard and embedded cartesian genetic programming}, url = {http://www.cs.bham.ac.uk/~wbl/biblio/gecco2006/docs/p903.pdf}, volume = 1, year = 2006 } @inproceedings{roberts:2001:sevgpep, added-at = {2008-06-19T17:46:40.000+0200}, address = {San Francisco, California, USA}, author = {Roberts, Simon C. and Howard, Daniel and Koza, John R.}, biburl = {http://www.bibsonomy.org/bibtex/2199a32f671038e60f710904b0c9f3aed/brazovayeye}, booktitle = {2001 Genetic and Evolutionary Computation Conference Late Breaking Papers}, editor = {Goodman, Erik D.}, interhash = {b629f8cb47490d200b7886b3c4a85861}, intrahash = {199a32f671038e60f710904b0c9f3aed}, keywords = {algorithms, automatically define functions genetic programming,}, month = {9-11 July}, notes = {GECCO-2001LB}, pages = {359--365}, timestamp = {2008-06-19T17:46:40.000+0200}, title = {Subtree Encapsulation Versus {ADFs} in Genetic Programming for the Even-5-Parity Problem}, year = 2001 } @inproceedings{vanbelle:2002:gecco, added-at = {2008-06-19T17:35:00.000+0200}, address = {New York}, author = {{Van Belle}, Terry and Ackley, David H.}, biburl = {http://www.bibsonomy.org/bibtex/282699a214957cf89108e599eff34dafb/brazovayeye}, booktitle = {GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference}, editor = {Langdon, W. B. and Cant{\'u}-Paz, E. and Mathias, K. and Roy, R. and Davis, D. and Poli, R. and Balakrishnan, K. and Honavar, V. and Rudolph, G. and Wegener, J. and Bull, L. and Potter, M. A. and Schultz, A. C. and Miller, J. F. and Burke, E. and Jonoska, N.}, interhash = {bbc70611dfc4be89f108fddc74a4888e}, intrahash = {82699a214957cf89108e599eff34dafb}, isbn = {1-55860-878-8}, keywords = {automatically code defined dynamic engineering engineering, environment, evolution evolvability, factoring, functions, genetic of programming, search-based software}, month = {9-13 July}, notes = {GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002) Wed, 28 Jan 2004 17:06:27 MST genetic_programming@yahoogroups.com Actually, the experiments in our GECCO 2002 paper _did_ use the standard tree depth < 17 cutoff on both branches, which is a form of parsimony pressure. This should have been reported, but unfortunately wasn't :-( Even though the typical RPBs generated were much shallower than the cutoff, it could have affected the RPB evolution, and probably helped keep down the ADF sizes somewhat.}, pages = {1383--1390}, publisher = {Morgan Kaufmann Publishers}, publisher_address = {San Francisco, CA 94104, USA}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Code Factoring And The Evolution Of Evolvability}, url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gecco2002/gecco-2002-25.pdf}, year = 2002 } @article{Uesaka:2003:CS, abstract = {This paper presents a synthesis method for infinite-impulse response (IIR) digital filter structures using genetic programming with automatically defined functions (GP-ADF). In the proposed method, digital filter structures are represented as S-expressions with subroutines, which are written directly from the set of difference equations. This paper also shows the condition for the constructing the S-expressions that represent the filter structures without delay-free loops. Numerical examples synthesize two-filter structures: the low-coefficient sensitivity fourth-order filter structure and the low-output roundoff noise second-order filter structure.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Uesaka, Kazuyoshi and Kawamata, Masayuki}, biburl = {http://www.bibsonomy.org/bibtex/2eef9df7aa10716f5407ab086c5a87e5e/brazovayeye}, interhash = {4d31bfb2cbbd4d29c63e08748366b3c2}, intrahash = {eef9df7aa10716f5407ab086c5a87e5e}, issn = {1057-7130}, journal = {IEEE Transactions on Circuits and Systems {II}: Analog and Digital Signal Processing}, keywords = {IIR S-expressions, algorithms, automatically computability, defined difference digital effects, equations, errors, evolutionary filter filter, filters, fitness fourth-order function functions, genetic global infinite-impulse low-coefficient low-output matrices, matrix measure, method, noise, optimization, programming, representation, response roundoff sensitivity, structures, subroutines, synthesis transfer wordlength}, month = {December}, notes = {Inspec Accession Number: 7830391}, number = 12, pages = {977--983}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Evolutionary synthesis of digital filter structures using genetic programming}, volume = 50, year = 2003 } @article{uesaka:2000:sl2df, abstract = {This letter proposes a synthesis method for low coefficient sensitivity second-order IIR digital filter structures using genetic programming with automatically defined functions (GP-ADF). In this letter, digital filter structures are represented as S-expressions with subroutines. It is easy to generate syntactically valid S-expressions and perform the genetic operations, because the representation is suitable for GP. A numerical example uses the fitness measure, including the magnitude sensitivity, and demonstrates that the proposed method can synthesize efficiently very low coefficient sensitivity filter structures.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Uesaka, Kazuyoshi and Kawamata, Masayuki}, biburl = {http://www.bibsonomy.org/bibtex/23323cf81b527356bcb09651e618c32e5/brazovayeye}, interhash = {39c2b5326e1a918b5a68da720b7fb8b3}, intrahash = {3323cf81b527356bcb09651e618c32e5}, issn = {1070-9908}, journal = {IEEE Signal Processing Letters}, keywords = {ADF IIR S-expressions, algorithms, automatically coefficient defined digital filter filter, filters, fitness functions, genetic low magnitude measure, method, programming, second-order sensitivity sensitivity, synthesis}, month = {April}, number = 4, pages = {83--85}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Synthesis of low-sensitivity second-order digital filters using genetic programming with automatically defined functions}, url = {http://ieeexplore.ieee.org/iel5/97/18028/00833004.pdf}, volume = 7, year = 2000 } @techreport{qureshi:1996:eaRN, abstract = { The paradigm of agent based computing is becoming increasingly popular both in distributed artificial intelligence and as a general software engineering technique. The difficulty with agent based computing is that success depends not on the correctness of any one agent, but on the emergent behaviour arising from the interaction of a society of agents. As a consequence, the problem of programming agents is non trivial and poorly understood. In this paper we show that genetic programming can be used to automatically program agents which communicate and interact to solve problems. The programs evolved simulataneously define when and what to communicate, and how to use the communicated information to solve the given problem.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Gower Street, London, WC1E 6BT, UK}, author = {Qureshi, A.}, biburl = {http://www.bibsonomy.org/bibtex/2ff1c795cd62b81d4e620a82849adc3e1/brazovayeye}, institution = {UCL}, interhash = {936854a0cdbdd044405ab46af69f4c11}, intrahash = {ff1c795cd62b81d4e620a82849adc3e1}, keywords = {(ADF) AI, Agent Artificial Automatic Automatically Based Code Communication, Computing, Defined Distributed Evolution, Functions Generation, Learning, Machine Programming, algorithms, genetic programming,}, month = {January}, notes = {Submitted to GP96}, number = {RN/96/4}, size = {10 pages}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Evolving Agents}, type = {Research Note}, url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/AQ.gp96.ps.gz}, year = 1996 } @inproceedings{Langdon:1996:usedata, abstract = {Provision of appropriately structured memory is shown, in some cases, to be advantageous to genetic programming (GP) in comparison with directly addressable indexed memory. Three ``classic'' problems are solved. The first two require the GP to distinguish between sentences that are in a context free language and those that are not given positive and negative training examples of the language. The two languages are, correctly nested brackets and a Dyck language (correctly nested brackets of different types). The third problem is to evaluate integer Reverse Polish (postfix) expressions. Comparisons are made between GP attempting to solve these problems when provided with indexed memory or with stack data structures.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Stanford University, CA, USA}, author = {Langdon, W. B.}, biburl = {http://www.bibsonomy.org/bibtex/2236646275442c265c2b16ffaf04ad437/brazovayeye}, booktitle = {Genetic Programming 1996: Proceedings of the First Annual Conference}, editor = {Koza, John R. and Goldberg, David E. and Fogel, David B. and Riolo, Rick L.}, interhash = {ef5b904f09b1956232b501d21898fb46}, intrahash = {236646275442c265c2b16ffaf04ad437}, keywords = {(ADF), Artificial Automatic Automatically CFG, Data Defined Demes Dyck Evolution, Expressions, Functions Learning, Machine Object Oriented Pareto Polish Programming, Push Reverse Stack, Structures, algorithms, automatic brackets, code context down fitness, free generation, genetic grammar induction, language language, matched programming,}, month = {28--31 July}, notes = {GP-96. Replaces \cite{Langdon:1996:usedataRN}}, pages = {141--148}, publisher = {MIT Press}, size = {9 pages}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Using Data Structures within Genetic Programming}, url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL.gp96.ps}, year = 1996 } @techreport{Langdon:1996:usedataRN, abstract = {In earlier work we showed that GP can automatically generate simple data types (stacks, queues and lists). The results presented herein show, in some cases, provision of appropriately structured memory can indeed be advantageous to GP in comparison with directly addressable indexed memory. Three ``classic'' problems are solved. The first two require the GP to distinguish between sentences that are in a language and those that are not given positive and negative training examples of the language. The two languages are, correctly nested brackets and a Dyck language (correctly nested brackets of different types). The third problem is to evaluate integer Reverse Polish (postfix) expressions. Comparisons are made between GP attempting to solve these problems when provided with indexed memory or with stack data structures.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Gower Street, London, WC1E 6BT, UK}, author = {Langdon, W. B.}, biburl = {http://www.bibsonomy.org/bibtex/2875532499f61f08ebfd594c46d591f8a/brazovayeye}, institution = {UCL}, interhash = {ef5b904f09b1956232b501d21898fb46}, intrahash = {875532499f61f08ebfd594c46d591f8a}, keywords = {(ADF), Artificial Automatic Automatically Data Defined Demes Evolution, Expressions, Functions Learning, Machine Object Oriented Pareto Polish Programming, Push Reverse Stack, Structures, algorithms, automatic code context down fitness, free generation, genetic induction, language programming,}, month = {January}, notes = {Accepted for presentation at GP96. Updated version in proceedings and url, see \cite{Langdon:1996:usedata}}, number = {RN/96/1}, size = {10 pages}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Using Data Structures within Genetic Programming}, type = {Research Note}, url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL.gp96.ps}, year = 1996 } @inproceedings{Langdon:1995:GPdata, abstract = {Genetic programming (GP) is a subclass of genetic algorithms (GAs), in which evolving programs are directly represented in the chromosome as trees. Recently it has been shown that programs which explicitly use directly addressable memory can be generated using GP. It is established good software engineering practice to ensure that programs use memory via abstract data structures such as stacks, queues and lists. These provide an interface between the program and memory, freeing the program of memory management details which are left to the data structures to implement. The main result presented herein is that GP can automatically generate stacks and queues. Typically abstract data structures support multiple operations, such as put and get. We show that GP can simultaneously evolve all the operations of a data structure by implementing each such operation with its own independent program tree. That is, the chromosome consists of a fixed number of independent program trees. Moreover, crossover only mixes genetic material of program trees that implement the same operation. Program trees interact with each other only via shared memory and shared ``Automatically Defined Functions'' (ADFs). ADFs, ``pass by reference'' when calling them, Pareto selection, ``good software engineering practice'' and partitioning the genetic population into ``demes'' where also investigated whilst evolving the queue in order to improve the GP solutions.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Pittsburgh, PA, USA}, author = {Langdon, W. B.}, biburl = {http://www.bibsonomy.org/bibtex/2dc3d5118a3350b336a0742d6040f7638/brazovayeye}, booktitle = {Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA95)}, editor = {Eshelman, L.}, interhash = {8da93f3c7dffaeb910b499ec22ea2161}, intrahash = {dc3d5118a3350b336a0742d6040f7638}, isbn = {1-55860-370-0}, keywords = {(ADF), (FIFO) Artificial Automatic Automatically Data Defined Demes Evolution, First-in Functions Learning, Machine Object Oriented Pareto Programming, Push Queue, Stack, Structures, algorithms, down first-out fitness, genetic programming,}, month = {15-19 July}, notes = {Discussed on GP mailing list 6--13 Jan 95, subj: GPdata. Mainly as \cite{Langdon:1995:GPdataRN} but with more details on pareto selection}, pages = {295--302}, publisher = {Morgan Kaufmann}, publisher_address = {San Francisco, CA, USA}, size = {8 pages}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Evolving Data Structures Using Genetic Programming}, url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/GPdata_icga-95.ps}, year = 1995 } @techreport{Langdon:1995:GPdataRN, abstract = {Genetic programming (GP) is a subclass of genetic algorithms (GAs), in which evolving programs are directly represented in the chromosome as trees. Recently it has been shown that programs which explicitly use directly addressable memory can be generated using GP. It is established good software engineering practice to ensure that programs use memory via abstract data structures such as stacks, queues and lists. These provide an interface between the program and memory, freeing the program of memory management details which are left to the data structures to implement. The main result presented herein is that GP can automatically generate stacks and queues. Typically abstract data structures support multiple operations, such as put and get. We show that GP can simultaneously evolve all the operations of a data structure by implementing each such operation with its own independent program tree. That is, the chromosome consists of a fixed number of independent program trees. Moreover, crossover only mixes genetic material of program trees that implement the same operation. Program trees interact with each other only via shared memory and shared ``Automatically Defined Functions'' (ADFs). ADFs, ``pass by reference'' when calling them, Pareto selection, ``good software engineering practice'' and partitioning the genetic population into ``demes'' where also investigated whilst evolving the queue in order to improve the GP solutions.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Gower Street, London, WC1E 6BT, UK}, author = {Langdon, W. B.}, biburl = {http://www.bibsonomy.org/bibtex/2b52703d8dc168e49002e9fea722667b2/brazovayeye}, institution = {UCL}, interhash = {8da93f3c7dffaeb910b499ec22ea2161}, intrahash = {b52703d8dc168e49002e9fea722667b2}, keywords = {(ADF), (FIFO) Artificial Automatic Automatically Data Defined Demes Evolution, First-in Functions Learning, Machine Object Oriented Pareto Programming, Push Queue, Stack, Structures, algorithms, down first-out fitness, genetic programming,}, month = {January}, notes = {Discussed on GP mailing list 6--13 Jan 95, subj:GPdata. Presented at ICGA-95. Reworked into \cite{Langdon:1995:GPdata}}, number = {RN/95/1}, size = {10 pages}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Evolving Data Structures Using Genetic Programming}, type = {Research Note}, url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/GPdata_icga-95.ps}, year = 1995 } @incollection{koza:2003:GPTP, abstract = {Genetic programming can be used as an automated invention machine to synthesise designs for complex structures. In particular, genetic programming has automatically synthesized complex structures that infringe, improve upon, or duplicate the functionality of 21 previously patented inventions (including analog electrical circuits, controllers, and mathematical algorithms). Genetic programming has also generated two patentable new inventions (involving controllers). Genetic programming has also generated numerous additional human-competitive results involving the design of quantum computing circuits as well as other substantial results involving antennae, networks of chemical reactions (metabolic pathways), and genetic networks. We believe that these results are the direct consequence of a group of techniques, many unique to genetic programming, that facilitate the automatic synthesis of complex structures. These techniques include automatic reuse, parameterised reuse, parameterised topologies, and developmental genetic programming. The paper describes these techniques and how they contribute to automated design.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Koza, John R. and Streeter, Matthew J. and Keane, Martin A.}, biburl = {http://www.bibsonomy.org/bibtex/24db598dd624748459e3e9349788d9b13/brazovayeye}, booktitle = {Genetic Programming Theory and Practise}, chapter = 14, editor = {Riolo, Rick L. and Worzel, Bill}, interhash = {02cf2f4c88fcccb479242240da6c4e94}, intrahash = {4db598dd624748459e3e9349788d9b13}, isbn = {1-4020-7581-2}, keywords = {Hierarchy, algorithms, architecture-altering automatically circuits, controllers defined development, functions, genetic iterations, loops, operations, parameterized programming, recursions, reuse, stores, topologies,}, pages = {221--237}, publisher = {Kluwer}, size = {14 pages}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Automated Synthesis by Means of Genetic Programming of Complex Structures Incorporating Reuse, Hierarchies, Development, and Parameterized Toplogies}, url = {http://www.genetic-programming.com/jkpdf/gptp2003.pdf}, year = 2003 } @inproceedings{howard:2002:gecco, added-at = {2008-06-19T17:35:00.000+0200}, address = {New York}, author = {Howard, Daniel and Roberts, Simon C. and Ryan, Conor}, biburl = {http://www.bibsonomy.org/bibtex/296ab4e229652eb7210d89a8eb2cc8dff/brazovayeye}, booktitle = {GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference}, editor = {Langdon, W. B. and Cant{\'u}-Paz, E. and Mathias, K. and Roy, R. and Davis, D. and Poli, R. and Balakrishnan, K. and Honavar, V. and Rudolph, G. and Wegener, J. and Bull, L. and Potter, M. A. and Schultz, A. C. and Miller, J. F. and Burke, E. and Jonoska, N.}, interhash = {7fd2fbd018fdaa3ff01735efa35fd3bc}, intrahash = {96ab4e229652eb7210d89a8eb2cc8dff}, isbn = {1-55860-878-8}, keywords = {algorithms, analysis, automatically crawler, data defined detection functions, genetic image machine programming, target vision,}, month = {9-13 July}, notes = {GECCO-2002. A joint meeting of the eleventh International Conference on Genetic Algorithms (ICGA-2002) and the seventh Annual Genetic Programming Conference (GP-2002)}, pages = {756--763}, publisher = {Morgan Kaufmann Publishers}, publisher_address = {San Francisco, CA 94104, USA}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Machine Vision: Exploring Context With Genetic Programming}, url = {http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gecco2002/gecco-2002-14.pdf}, year = 2002 } @inproceedings{Chie:gecco06lbp, abstract = {automatically defined terminal (ADT) to keep ready and stable building blocks growing into complex structure. The idea is originated from the functional modularity approach. ADT is tested in an agent-based innovation model to see how it works and whether there is any improvement in searching new commodities for commercialising in the market; hence the market represents an environment for nourishing the development during innovative process. This paper will not only show how the capable producers with ADT work, but also how market selection plays an important role in the evolution of innovation. In other word, the agent-based modelling approach will present the evolutionary dynamic of interaction between producers and consumers in a commodity market.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {Seattle, WA, USA}, author = {Chie, Bin-Tzong and Wang, Chih-Chien}, biburl = {http://www.bibsonomy.org/bibtex/2ed715c3e5eed6ff1794f286355c3561b/brazovayeye}, booktitle = {Late breaking paper at Genetic and Evolutionary Computation Conference {(GECCO'2006)}}, editor = {Grahl, J{\"{o}}rn}, interhash = {de261533a74bae803882cd3147cf1769}, intrahash = {ed715c3e5eed6ff1794f286355c3561b}, keywords = {Agent-Based Automatically Defined Modeling Terminal, algorithms, genetic programming,}, month = {8-12 July}, notes = {Distributed on CD-ROM at GECCO-2006}, timestamp = {2008-06-19T17:35:00.000+0200}, title = {Model for Evolutionary Technology - An Automatically Defined Terminal Approach}, year = 2006 }