Genetic Programming and Genetic Algorithms

We are interested in adapting genetic algorithm and genetic programming techniques to a number of difficult problems:

Current Work

[1]
Gayan Wijesinghe. Loops in Genetic Programming. PhD Thesis, RMIT, School of Computer Science and Information Technology, 2006. In progress, full time.

Completed Theses

[1]
Xiang Li. Utilising Restricted For-Loops in Genetic Programming. PhD Thesis, RMIT, Department of Computer Science, 2007. (PDF, 1865980 bytes)

[2]
Jeff Riley. Evolving Fuzzy Rukes for Goal-Scoring Behaviour in a Robot Soccer Environment. Ph. D. Thesis, RMIT, School of Computer Science and Information Technology, 2005. (PDF, 19381751 bytes)

[3]
Tom Loveard. Genetic Programming Methods for Classification Problems. PhD Thesis, RMIT, Department of Computer Science, 2003. (PDF, 1943002 bytes)

[4]
Andy Song. Texture Classification: A Genetic Programming Approach. PhD Thesis, RMIT, Department of Computer Science, 2003.

[5]
Ken Gardiner. Application of Genetic Programming to Rule Production for Telecommunication Network Event Correlation. Masters thesis, RMIT, Department of Computer Science, 1999.

[6]
Nelson Wu. Evolving Similarity Functions for Code Plagiarism Detection. Honours Thesis, RMIT, School of Computer Science and Information Technology, 2007. (PDF, 281467 bytes)

[7]
Michael Foster. The Program Structure of Genetic Programming Trees. Honours Thesis, RMIT, School of Computer Science and Information Technology, 2005. (PDF, 1767563 bytes)

[8]
Teja Nanduri. Comparison of the Effectiveness of Decimation and Automatically Defined Functions. Minor Thesis, RMIT, Department of Computer Science, 2005. (PDF, 289008 bytes)

[9]
Andrei Bajurnow. Layered Learning for Simple Soccer. Minor Thesis, RMIT, Department of Computer Science, 2004. (PDF, 569911 bytes)

[10]
Tania Binos. Evolving Neural Network Architecture and Weights Using An Evolutionary Algorithm. Minor Thesis, RMIT, Department of Computer Science, 2002. (PDF, 318460 bytes)

[11]
Shi Yoon Lai. Development of a Dribble Behaviour for Robot Soccer Using Neuro Evolution. Minor Thesis, RMIT, Department of Computer Science, 2001. (PDF, 560313 bytes)

[12]
Michael Matkovic. Co-evolving Competitive Behaviours in Genetic Programming. Honours Thesis, RMIT, Department of Computer Science, 2002. (Gzipped PostScript, 33 pages, 406087 bytes)

[13]
Dylan Mahwinney. Prevention of Premature Convergence in Genetic Programming. Honours Thesis, RMIT, Department of Computer Science, 2000. (Gzipped PostScript, 39 pages, 195809 bytes)

[14]
Nathan Deklepper. High Level Functions in Genetic Programming for Robosoccer. Hons Thesis, RMIT, Department of Computer Science, 1999. (Gzipped PostScript, 28 pages, 157234 bytes)

[15]
Peter Wilson. Development of a Team of Soccer Playing Robots by Genetic Programming. Honours Thesis, RMIT, Department of Computer Science, 1998. (Gzipped PostScript, 27 pages, 131870 bytes)

[16]
Jason Leonard. Interactive Game Scheduling with Genetic Algorithms. Minor thesis, RMIT, Department of Computer Science, 1997. (PDF, 287250 bytes)

[17]
Domenico Lombardo. A Fuzzy Expert System For Assisting the Creation of Structural Dynamic Finite Element Models. Minor thesis, RMIT, Department of Computer Science, 1997. (PDF, 568211 bytes)

[18]
Jim Ricketts. Optimizing Newspaper Advertisement Layout with Genetic Algorithms. Minor thesis, RMIT, Department of Computer Science, 1997. (PDF, 657286 bytes)

[19]
Jeff Riley. An Evolutionary Approach to Training Feed Forward and Recurrent Neural Networks. Minor thesis, RMIT, Department of Computer Science, 1997. (PDF, 396251 bytes)

[20]
Geoff Woods. A Hybrid Genetic Algorithm that Adapts to Binary and Real Coded Operators. Minor thesis, RMIT, Department of Computer Science, 1996. (PDF, 813513 bytes)

[21]
Rajendra Krishnan. 2DELTA-GANN: A new method of training neural networks using genetic algorithms. Enhanced minor thesis, RMIT, Department of Computer Science, Melbourne, April 1994. (Gzipped PostScript, 173715 bytes)

Selected Papers Describing This Work

[1]
Perry Barile, Vic Ciesielski, and Karen Trist. Non-photorealistic rendering using genetic programming. In Xiaodong Li et al., editor, SEAL 2008: Proceedings of the 7th International Conference on Simulated Evolution and Learning, pages 299-306. LNCS 5361, Springer-Verlag, Berlin, 2008. (PDF)

[2]
Gayan Wijesinghe and Vic Ciesielski. Experiments with indexed for-loops in genetic programming. In GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pages 1347-1348, New York, NY, USA, 2008. ACM. (PDF)

[3]
Vic Ciesielski, Nelson Wu, and Seyed Tahaghoghi. Evolving similarity functions for code plagiarism detection. In GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pages 1453-1460, New York, NY, USA, 2008. ACM. (PDF)

[4]
Jeff Riley and Vic Ciesielski. Analysing the difficulty of learning goal-scoring behaviour for robot soccer. In Pedro Lima, editor, Robotic Soccer, pages 307-336. I-Tech Education and Publishing, Vienna, 2007.

[5]
Vic Ciesielski. Book Review: Linear Genetic Programming, Markus Brameier and Wolfgang Banzhaf. Genetic Programming and Evolvable Machines, 9(1). Book Review.

[6]
Gayan Wijesinghe and Vic Ciesielski. Using restricted loops in genetic programming for image classification. In Proceedings of the 2007 Congress on Evolutionary Computation (CEC2007, pages 4569-4576, Singapore, 2007.

[7]
Jeff Riley and Vic Ciesielski. Analysis of the difficulty of learning goal scoring behaviour for robot soccer. In Maarten Keijzer et al., editor, Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO2006), volume 2, pages 1569-1576. ACM Press, July 2006. (PDF)

[8]
Dharma Teja Nanduri and Vic Ciesielski. Comparison of the effectiveness of decimation and automatically defined functions. In Rajiv Khosla, Robert Howlett, and Lakhmi Jain, editors, Ninth International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES05), Lecture Notes in Artificial Intelligence, Volume 3683, pages III:540-546. Springer, September 2005.

[9]
Daniel Parrot, Xiaodong Li, and Vic Ciesielski. Multi-objective techniques in genetic programming for evolving classifiers. In Proceedings of the 2005 Congress on Evolutionary Computation (CEC2005), pages 1141-1148. IEEE Press, September 2005.

[10]
Xiang Li and Vic Ciesielski. An analysis of explicit loops in genetic programming. In Proceedings of the 2005 Congress on Evolutionary Computation (CEC2005, pages 2522-2529. IEEE Press, September 2005.

[11]
Vic Ciesielski and Xiang Li. Analysis of genetic programming runs. In R. McKay, editor, Asia-Pacific Workshop on Genetic Programming, December 2004. (PDF, 4671205 bytes)

[12]
Xiang Li and Vic Ciesielski. Using loops in genetic programming for a two class binary image classification problem. In G. Webb and X. Yu, editors, Proceedings of the 2004 Australian Joint Conference on Artificial Intelligence, Lecture Notes in Artificial Intelligence 3339, pages 898-909. Springer, December 2004. (PDF, 241506 bytes)

[13]
Andrei Bajurnow and Vic Ciesielski. Layered learning for evolving goal scoring behaviour in soccer players. In Garrison Greenwood, editor, Proceedings of the 2004 Congress on Evolutionary Computation (CEC2004), volume 2, pages 1828-1835. IEEE, June 2004. (PDF, 136533 bytes)

[14]
Vic Ciesielski and Xiang Li. Experiments with explicit for-loops in genetic programming. In Garrison Greenwood, editor, Proceedings of the 2004 Congress on Evolutionary Computation (CEC2004), volume 1, pages 494-503. IEEE, June 2004. (PDF, 277713 bytes)

[15]
Yaniv Bernstein, Xiaodong Li, Vic Ciesielski, and Andy Song. Multiobjective parsimony enforcement for superior generalisation performance. In Garrison Greenwood, editor, Proceedings of the 2004 Congress on Evolutionary Computation (CEC2004), volume 1, pages 83-89. IEEE, June 2004. (PDF, 416111 bytes)

[16]
Jeff Riley and Vic Ciesielski. Evolution of fuzzy rule based controllers for dynamic environments. In Kay Chen Tan, Meng Hiot Lim, Xin Yao, and Lipo Wang, editors, Recent Advances in Simulated Evolution and Learning, volume 2 of Advances in Natural Computation, chapter 23, pages 426-445. World Scientific, 2004.

[17]
Vic Ciesielski and Xiang Li. Pyramid search: Finding solutions for deceptive problems quickly in genetic programming. In Sarker R. et al., editor, Proceedings of the 2003 Congress on Evolutionary Computation (CEC2003), volume 2, pages 936-943. IEEE Press, December 2003. (PDF, 101175 bytes)

[18]
Thomas Loveard and Vic Ciesielski. Genetic programming for classification: An analysis of convergence behaviour. In Bob McKay and John Slaney, editors, Proceedings of the 15th Australian Joint Conference on Artificial Intelligence (AI2002), Lecture Notes in Computer Science 2557, pages 309-320, Canberra, December 2002. Springer. (PDF, 177840 bytes)

[19]
Thomas Loveard and Vic Ciesielski. Employing nominal attributes in classification using genetic programming. In Lipo Wang, Kay Chen Tan, Takeshi Furuhashi, Jong-Hwan Kim, and Xin Yao, editors, Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL02), pages 487-491, Singapore, November 2002. IEEE. (PDF, 78096 bytes)

[20]
Jeff Riley and Vic Ciesielski. Evolving fuzzy rules for reactive agents in dynamic environments. In Lipo Wang, Kay Chen Tan, Takeshi Furuhashi, Jong-Hwan Kim, and Xin Yao, editors, Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL02), pages 124-130, Singapore, November 2002. IEEE. (PDF, 472475 bytes)

[21]
Vic Ciesielski and Dylan Mawhinney. Prevention of early convergence in genetic programming by replacement of similar programs. In Xin Yao, editor, Proceedings of the 2002 Congress on Evolutionary Computation, volume 1, pages 67-72, Honolulu, May 2002. IEEE.

[22]
Thomas Loveard. Genetic programming with meta-search: Searching for a successful population within the classification domain. In Conor Ryan, Terence Soule, Maarten Keijzer, Edward Tsang, Riccardo Poli, and Ernesto Costa, editors, Proceedings of the 6th European Conference on Genetic Programming (EuroGP 2003), pages 119-129, Berlin, 2003. Springer. Winner, Best Student Paper. (PDF, 118284 bytes)

[23]
Andrew Innes, Vic Ciesielski, John Mamutil, Sabu John, and Alan Harvey. Landmark detection for cephalometric radiology images using genetic programming. In Ruhul Sarker, Bob McKay, Mitsuo Gen, and Akira Namatame, editors, Proceedings of the 6th Australia-Japan Joint Workshop on Intellignet and Evolutionary Systems, pages 125-132, Canberra, November 2002. (PDF, 398326 bytes)

[24]
Thomas Loveard and Vic Ciesielski. Representing classification problems in genetic programming. In Jong-Hwan Kim, editor, Proceedings of the 2001 Congress on Evolutionary Computation, pages 1070-1077, Seoul, South Korea, May 2001. IEEE. (Gzipped PostScript, 8 pages, 42839 bytes)

[25]
Vic Ciesielski and Shi Yoon Lai. Developing a dribble-and-score behaviour for robot soccer using neuro evolution. In Peter Wigham, editor, Proceedings of the 5th Australia-Japan Joint Workshop on Intellignet and Evolutionary Systems, pages 70-78, Dunedin, New Zealand, November 2001. University of Otago and Ashikaga Institute of Technology. (PDF, 131460 bytes)

[26]
Vic Ciesielski, Dylan Mawhinney, and Peter Wilson. Genetic programming for robot soccer. In Andreas Birk, Silvia Coradeschi, and Satoshi Tadokoro, editors, Proceedings of the RoboCup 2001 International Symposium, Lecture Notes in Artificial Intelligence 2377, pages 319-324. Springer, 2002. (PDF, 268976 bytes)

[27]
Andy Song, Thomas Loveard, and Vic Ciesielski. Towards genetic programming for texture classification. In Markus Sumpter, Dan Corbett, and Mike Brooks, editors, AI 2001: Advances in Artificial Intelligence, Proceedings of the 14th Australian Joint Conference on Artificial Intelligence,Lecture Notes in Artificial Intelligence 2256, pages 461-472, Berlin, December 2001. Springer-Verlag. (Gzipped PostScript, 12 pages, 305417 bytes)

[28]
Victor Ciesielski and Peter Wilson. Developing a team of soccer playing robots by genetic programming. In Bob Mckay, Yasuhiro Tsujimura, Ruhul Sarker, Akira Namatame, Xin Yao, and Mitsuo Gen, editors, Proceedings of The Third Australia-Japan Joint Workshop on Intelligent and Evolutionary Systems, pages 101-108, Canberra, November 1999. Australian Defence Force Academy, School of Computer Science. (Gzipped PostScript, 8 pages, 92581 bytes)

[29]
Victor Ciesielski and Jeff Riley. An evolutionary approach to training feed forward and recurrent neural networks. In L. C. Jain and R. K. Jain, editors, Proceedings of the Second International Conference on Knowledge Based Intelligent Electronic Systems (KES'98, pages 596-602, Adelaide, April 1998. IEEE. (PDF, 105497 bytes)

[30]
Victor Ciesielski and Paul Scerri. Real time genetic scheduling of aircraft landing times. In David Fogel, editor, The IEEE International Conference on Evolutionary Computation (ICEC98), pages 360-364, Anchorage, May 1998. (PDF, 161633 bytes)

[31]
Victor Ciesielski and Paul Scerri. An anytime algorithm for scheduling of aircraft landing times using genetic algorithms. Australian Journal of Intelligent Information Processing Systems, 4(3/4):206-213, Spring/Summer (Southern Hemisphere) 1997. (Gzipped PostScript, 8 pages, 65074 bytes)

[32]
Vladimir Brusic, Christian Schonbach, Masafumi Takiguchi, Victor Ciesielski, and Leonard Harrison. Application of Genetic Search in the Derivation of Matrix Models of Peptide Binding to MHC Molecules . In Terry Gaasterland, Peter Karp, Kevin Karplus, Christos Ouzounis, Chris Sanders, and Alfonso Valencia, editors, Proceedings of the Fifth International Conference on Intelligent Systems for Molecular Biology, pages 75-83, Menlo Park, California, June 1997. AAAI Press. (Gzipped PostScript, 9 pages, 61130 bytes)

[33]
Victor Ciesielski, Jihan Zhu, John Spicer, and Claire Franklin. A comparison of image processing techniques and neural networks for an automated visual inspection problem. In Anthony Adams and Leon Sterling, editors, Proceedings of the 5th Joint Australian Conference on Artificial Intellignece, pages 147-152, Hobart, Tasmania, 1992. World Scientific. (PDF, 847110 bytes)

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