Rule-based genetic programming

Proceedings of the Bio-Inspired Models of Network, Information, and Computing Systems, Bionetics 2007

Volumn , Issue , 2007, Pages 8-15

  Weise, Thomas ^a   Zapf, Michael ^a   Geihs, Kurt ^a  

^a UNIVERSITY OF KASSEL   (Germany)

Author keywords

Critical section; Distributed algorithms; Epistasis; Genetic Programming; RBGP; Rule based Genetic Programming

Indexed keywords

COMPUTER PROGRAMMING; COMPUTER SYSTEMS; GENETIC ALGORITHMS; NETWORK PROTOCOLS; SENSOR NETWORKS;

CRITICAL SECTION; DISTRIBUTED ALGORITHMS; EPISTASIS; RBGP; RULE-BASED GENETIC PROGRAMMING;

GENETIC PROGRAMMING;

EID: 53149117498     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIMNICS.2007.4610073     Document Type: Conference Paper

References (46)

1. W. Banzhaf. Genotype-phenotype-mapping and neutral variation - A case study in genetic programming. In Parallel Problem Solving from Nature III, volume 866.
2. W. Banzhaf, P. Nordin, R. E. Keller, and F. D. Francone. Genetic Programming: An Introduction - On the Automatic Evolution of Computer Programs and Its Applications. Morgan Kaufmann Publishers, first edition, Nov. 1997.
3. W. Bateson. Mendel's Principles of Heredity. Cambridge University Press, Cambridge, 1909. 1930: fourth impression of the 1909 edition.
4. M. Brameier and W. Banzhaf. A comparison of linear genetic programming and neural networks in medical data mining. IEEE Transactions on Evolutionary Computation, 5(1):17-26, 2001.
5. W. N. Browne and C. Ioannides. Investigating scaling of an abstracted lcs utilising ternary and s-expression alphabets. In GECCO '07: Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation, pages 2759-2764, New York, NY, USA, 2007. ACM Press.
6. N. L. Cramer. A representation for the adaptive generation of simple sequential programs. In J. J. Grefenstette, editor, Proceedings of an International Conference on Genetic Algorithms and the Applications, pages 183-187, Carnegie-Mellon University, Pittsburgh, PA, USA, July 1985. Lawrence Erlbaum Associates, Inc.
7. M. de la Cruz Echeandía, A. O. de la Puente, and M. Alfonseca. Attribute Grammar Evolution, volume 3562/2005 of Lecture Notes in Computer Science, pages 182-191. Springer Berlin / Heidelberg, June 2005.
8. E. W. Dijkstra. Cooperating sequential processes. Technical report, Techniche Hogeschool Eindhoven, Techniche Hogeschool Eindhoven, 1965. About Dekker's Algorithm. Reprinted in: F. Genuys (ed.), Programming Languages, Academic Press, 1968, 43-112.
9. E. W. Dijkstra. Solution of a problem in concurrent programming control. Communications of the ACM, 8(9):569, 1965.
10. M. L. et al., editor. Proceedings of Automated Formal Methods 2006 (AFM 2006), Aug. 2006. Workshop on the tools PVM, SAL, and Yices.
11. R. M. Friedberg. A learning machine: Part i. IBM Journal of Research and Development, 2:2-13, Nov. 1958.
12. R. M. Friedberg, B. Dunham, and J. H. North. A learning machine: Part ii. IBM Journal of Research and Development, 3(3):282-287, Mar. 1959.
13. D. E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Longman Publishing Co., Inc. Boston, MA, USA, first edition, 1989.
14. N. X. Hoai. Solving trigonometric identities with tree adjunct grammar guided genetic programming. In A. Abraham and M. Köppen, editors, Hybrid Information Systems, Proceedings of First International Workshopon Hybrid Intelligent Systems, pages 339-351, Dec. 2001.
15. N. X. Hoai. A Flexible Representation for Genetic Programming: Lessons from Natural Language Processing. PhD thesis, School of Information Technology and Electrical Engineering University College, University of New South Wales, Australian Defence Force Academy, Dec. 2004.
16. J. Holland. Genetic algorithms. Scientific American, 267(1):44-50, July 1992.
17. J. H. Holland. Properties of the bucket brigade algorithm. In Proceedings of the International Conference on Genetic Algorithms and Their Applications, pages 1-7, Pittsburgh, PA, 1985.
18. J. H. Holland and A. W. Burks. Adaptive computing system capable oflearning and discovery. US Patent Issued on September 29, 1987, Current US Class 706/13, Genetic algorithm and genetic programming system 382/155, LEARNING SYSTEMS 706/62 MISCELLANEOUS, Foreign Patent References 8501601 WO Apr., 1985.
19. J. H. Holland and J. S. Reitman. Cognitive systems based on adaptive algorithms. In D. A. Waterman and F. Hayes-Roth, editors, Pattern directed inference systems, pages 313-329. Academic Press, New York, NY, 1978.
20. Reprinted in: Evolutionary Computation. The Fossil Record. David B. Fogel (Ed.) IEEE Press, 1998. ISBN: 0-7803-3481-7.
21. H. Hörner. A C++ class library for gp: Vienna university of economics genetic programming kernel (release 1.0, operating instructions). Technical report, Vienna University of Economics, May 29 1996.
22. R. E. Keller and W. Banzhaf. Genetic programming using genotype-phenotype mapping from linear genomes into linear phenotypes. In J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, editors, Genetic Programming 1996: Proceedings of the First Annual Conference, pages 116-122, Stanford University, CA, USA, 1996. MIT Press.
23. R. E. Keller and W. Banzhaf. Genetic programming using mutation, reproduction and genotype-phenotype mapping from linear binary genomes into linear lalr(1) phenotypes. In J. R. Koza, D. E. Goldberg, D. B. Fogel, and R. L. Riolo, editors, Genetic Programming 1996: Proceedings of the First Annual Conference, pages 116-122, Stanford University, CA, USA, Jan. 1996. MIT Press.
24. J. R. Koza. Genetic Programming, On the Programming of Computers by Means of Natural Selection. A Bradford Book, The MIT Press, Cambridge, Massachusetts, 1992 first edition, 1993 second edition, 1992.
25. S. S. Lam. Delay analysis of a time division multiple access (tdma) channel. IEEE Transactions on Communications (legacy, pre - 1988), 25:1489-1494, Dec. 1977. NASA STI/Recon Technical Report A, volume 78, December 1977, pp. 19522.
26. L. Lamport. Time, clocks, and the ordering of events in a distributed system. Communications of the ACM, 21(7):558-565, 1978.
27. P. L. Lanzi and A. Perrucci. Extending the representation of classifier conditions part ii: From messy coding to s-expressions. In W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith, editors, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 99), pages 345-352. Morgan Kaufmann, July 1999.
28. M. Maekawa. An algorithm for mutual exclusion in decentralized systems. ACM Trans. Comput. Syst., 3(2):145-159, 1985.
29. B. Naudts. Measuring GA-hardness. PhD thesis, Antwerpen, Netherlands, 1998.
30. P. Nordin. A compiling genetic programming system that directly manipulates the machine code. pages 311-331, 1994.
31. P. Nordin and W. Banzhaf. Complexity compression and evolution. In L. Eshelman, editor, Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA95), pages 310-317, Pittsburgh, PA, USA, July 1995. Morgan Kaufmann.
32. M. O'Neill. Grammatical evolution. In Proceedings of the Fifth Research Conference of the Deptartment of Computer Science and Information Systems, University of Limerick, Sept. 1998.
33. G. Ricart and A. K. Agrawala. An optimal algorithm for mutual exclusion in computer networks. Communications of the ACM, 24(1):9-17, Jan. 1981.
34. S. Ronald. Robust encodings in genetic algorithms: A survey of encoding issues. pages 43-48, Apr. 1997.
35. C. Ryan, J. J. Collins, and M. O'Neill. Grammatical evolution: Evolving programs for an arbitrary language. In W. Banzhaf, R. Poli, M. Schoenauer, and T. C. Fogarty, editors, Proceedings of the First European Workshop on Genetic Programming, volume 1391, pages 83-95, Paris, 1998. Springer-Verlag.
36. C. Ryan, M. O'Neill, and J. J. Collins. Grammatical evolution: Solving trigonometric identities. In Proceedings of Mendel 1998: 4th International Mendel Conference on Genetic Algorithms, Optimisation Problems, Fuzzy Logic, Neural Networks, Rough Sets, pages 111-119, Brno, Czech Republic, 1998. Technical University of Brno, Faculty of Mechanical Engineering.
37. R. Shipman. Genetic redundancy: Desirable or problematic for evolutionary adaptation? In Proceedings of 4th International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA), pages 1-11. Springer-Verlag, 1999.
38. R. Shipman, M. Shackleton, and I. Harvey. The use of neutral genotype-phenotype mappings for improved evolutionary search. BT Technology Journal, 18(4):103-111, 2000.
39. S. F. Smith. A learning system based on genetic adaptive algorithms. PhD thesis, University of Pittsburgh, 1980.
40. W. M. Spears and K. A. De Jong. Using genetic algorithms for supervised concept learning. In Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence, number IEEE Cat. No. 90CH2915-7, pages 335-341, Herndon, VA, 6-9 1990. IEEE Computer Society Press, Los Alamitos, CA.
41. T. Weise. Global Optimization Algorithms - Theory and Application. July 2007 edition, July 2007. This e-book is online available at http://www.it-weise.de/.
42. T. Weise and K. Geihs. Dgpf - an adaptable framework for distributed multi-objective search algorithms applied to the genetic programming of sensor networks. In B. Filipič and J. Šilc, editors, Proceedings of the Second International Conference on Bioinspired Optimization Methods and their Application, BIOMA 2006, International Conference on Bioinspired Optimization Methods and their Application (BIOMA), pages 157-166. Jožef Stefan Institute, Ljubljana, Slovenia, Oct. 2006.
43. T. Weise and K. Geihs. Genetic programming techniques for sensor networks. In Proceedings of 5. GI/ITG KuVS Fachgespräch\Drahtlose Sensornetze", pages 21-25, University of Kassel, July 2006.
44. T. Weise, K. Geihs, and P. A. Baer. Genetic programming for proactive aggregation protocols. In B. Beliczyński, A. Dzieliński, M. Iwanowski, and B. Ribeiro, editors, Proceedings of the 8th International Conference on Adaptive and Natural Computing Algorithms ICANNGA'07, Part 1, volume 4431 of Lecture Notes in Computer Science (LNCS), pages 167-173. Springer Berlin Heidelberg New York, Apr. 2007.
45. P. A. Whigham. Inductive bias and genetic programming. In A. M. S. Zalzala, editor, First International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, GALESIA, volume 414, pages 461-466, Sheffield, UK, 12-14 1995. IEE.
46. M. L. Wong and K. S. Leung. Combining genetic programming and inductive logic programming using logic grammars. In 1995 IEEE Conference on Evolutionary Computation, volume 2, pages 733-736, Perth, Australia, Nov. 1995. IEEE Press.