Automated feature selection in neuroevolution

Evolutionary Intelligence

Volumn 1, Issue 4, 2009, Pages 271-292

  Tan, Maxine ^a   Hartley, Michael ^b   Bister, Michel ^a   Deklerck, Rudi ^a  

^a VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

^b DownUnder GeoSolutions   (Australia)

Author keywords

Genetic algorithms evolution; Learning; Neural networks

Indexed keywords

EID: 84865033087     PISSN: 18645909     EISSN: 18645917     Source Type: Journal    
DOI: 10.1007/s12065-009-0018-z     Document Type: Article

References (49)

1. Zongker D, Jain A (1996) Algorithms for feature selection: an evaluation. In: Proceedings of the 13th international conference on pattern recognition. Vienna, Austria, pp 18-22
2. Kittler J (1978) Feature set search algorithms. In: Chen CH (ed) Pattern recognition and signal processing. Sijthoff and Noord-hoff, Alphen aan den Rijn, Netherlands, pp 41-60
3. Mao KZ (2002) Fast orthogonal forward selection algorithm for feature subset selection. IEEE Trans Neural Netw 13:1218-1224
4. Narendra PM, Fukunaga K (1977) A branch and bound algorithm for feature subset selection. IEEE Trans Comput c-26:917-922
5. Ferri FJ, Pudil P, Hatef M, Kittler J (1994) Comparative study of techniques for large-scale feature selection. In: Gelsema ES, Kanal LN (eds) Pattern recognition in practice IV. Elsevier Science B.V., Amsterdam, pp 403-413
6. Pudil P, Novovicova J, Kittler J (1994) Floating search methods in feature selection. Pattern Recognit Lett 15:1119-1125
7. Jain A, Zongker D (1997) Feature selection: evaluation, application, and small sample performance. IEEE Trans Pattern Anal Machine Intell 19:153-157
8. Kudo M, Sklansky J (2000) Comparison of algorithms that select features for pattern classifiers. Pattern Recognit 33:25-41
9. Kohavi R, John GH (1997) Wrappers for feature subset selection. Artif Intell 97:273-324
10. Langley P (1994) Selection of relevant features in machine learning. In: Proceedings of the AAAI fall symposium on relevance. AAAI Press, New Orleans
11. Bonnlander BV, Weigend AS (1994) Selecting input variables using mutual information and nonparametric density estimation. In: Proceedings of the 1994 international symposium on artificial neural networks (ISANN'94). Tainan, Taiwan, pp 42-50
12. Yang J, Honavar V (1998) Feature subset selection using a genetic algorithm. IEEE Intell Syst 13:44-49
13. Whiteson S, Stanley KO, Miikkulainen R (2004) Automatic feature selection in neuroevolution. In: Proceedings of the genetic and evolutionary computation conference (GECCO), Seattle, Washington, USA
14. Whiteson S, Stone P, Stanley KO, Miikkulainen R, Kohl N (2005) Automatic feature selection in neuroevolution. In: Proceedings of the genetic and evolutionary computation conference (GECCO), Washington, DC, USA
15. Stanley KO, Miikkulainen R (2002) Evolving neural networks through augmenting topologies. Evol Comput 10:99-127
16. Stanley KO, Miikkulainen R (2004) Competitive coevolution through evolutionary complexification. J Artif Intell Res 21:63-100
17. Langley P, Sage S (1994) Oblivious decision trees and abstract cases. In: Working notes of the AAAI-94 workshop on case-based reasoning. AAAI Press, Seattle, pp 113-117
18. Kelly JDK, Davis L (1991) Hybridizing the genetic algorithm and the k nearest neighbors classification algorithm. In: Belew RK, Booker LB (eds) Proceedings of the 4th international conference on genetic algorithms. Morgan Kaufmann, San Diego, pp 377- 383
19. Timin ME (1995) The robot auto racing simulator. Available via http://rars.sourceforge.net
20. Gomez F, Miikkulainen R (1998) 2-D pole balancing with recurrent evolutionary networks. In: Proceedings of the international conference on artificial neural networks (ICANN-98), Skovde, Sweden. Elsevier, New York
21. Gomez F, Miikkulainen R (1997) Incremental evolution of complex general behavior. Adapt Behav 5:317-342
22. Gruau F, Whitley D, Pyeatt L (1996) A comparison between cellular encoding and direct encoding for genetic neural networks. In: Koza JR, Goldberg DE, Fogel DB, Riolo, RL (eds) Proceedings of the first annual conference on genetic programming, Cambridge, MA, pp 81-89
23. Stanley KO (2004) Efficient evolution of neural networks through complexification. PhD thesis, The University of Texas at Austin
24. Harvey I (1992) Species adaptation genetic algorithms: a basis for a continuing SAGA. In: Varela FJ, Bourgine P (eds) Proceedings of the 1st European conference on artificial life, toward a practice of autonomous systems. MIT Press/Bradford Books, Cambridge, pp 346-354
25. Cliff D, Harvey I, Husbands P (1992) Incremental evolution of neural network architectures for adaptive behaviour. Technical report CSRP256, School of Cognitive and Computing Sciences, University of Sussex, UK
26. Gomez FJ, Miikkulainen R (1999) Solving non-markovian control tasks with neuroevolution. In: Proceedings of the international joint conference on artificial intelligence. Stockholm, Sweden. Morgan Kaufmann, Denver
27. Saravanan N, Fogel DB (1995) Evolving neural control systems. IEEE Expert 10(3):23-27
28. Wieland AP (1991) Evolving neural network controllers for unstable systems. In: Proceedings of the international joint conference on neural networks, Seattle, WA. Piscataway, New Jersey, pp 667-673
29. Yao X (1999) Evolving artificial neural networks. Proc IEEE 87:1423-1447
30. Moriarty DE, Miikkulainen R (1996) Efficient reinforcement learning through symbiotic evolution. Machine Learn 22:11-32
31. Radcliffe NJ (1993) Genetic set recombination and its application to neural network topology optimization. Neural Comput Appl 1:67-90
32. Dasgupta D, McGregor D (1992) Designing application-specific neural networks using the structured genetic algorithm. In: Proceedings of the international conference on combinations of genetic algorithms and neural networks. IEEE Computer Society Press, USA, pp 87-96
33. Pujol JCF, Poli R (1997) Evolution of the topology and the weights of neural networks using genetic programming with a dual representation. Technical report CSRP-97-7, School of Computer Science, The University of Birmingham, Birmingham B15 2TT, UK
34. Gruau F (1993) Genetic synthesis of modular neural networks. In: S. Forrest (ed) Proceedings of the fifth international conference on genetic algorithms. Morgan Kaufmann, San Mateo, CA, pp 318-325
35. Angeline PJ, Saunders GM, Pollack JB (1993) An evolutionary algorithm that constructs recurrent neural networks. IEEE Trans Neural Netw 5:54-65
36. Wieland A (1991) Evolving neural network controllers for unstable systems. In: Proceedings of the international joint conference on neural networks. Piscataway, New Jersey, pp 667-673
37. Stanley KO, Bryant BD, Miikkulainen R (2005) Real-time neu-roevolution in the NERO video game. IEEE Trans Evol Comput 9:653-668
38. Stanley KO, Miikkulainen R (2004) Evolving a roving eye for go. In: Proceedings of the genetic and evolutionary computation conference (GECCO). Springer, New York, pp 1226-1238
39. Schlessinger E, Bentley PJ, Lotto RB (2005) Analysing the evolvability of neural network agents through structural mutations. In: Capcarrere M (ed) Proceedings of the European conference on artificial life (ECAL 2005). Springer, Berlin, pp 312-321
40. Yao X, Liu Y (1996) Towards designing artificial neural networks by evolution. Appl Math Comput 91:83-90
41. Kohl N, Stanley K, Miikkulainen R, Samples M, Sherony R (2006) Evolving a real-world vehicle warning system. In: Proceedings of the genetic and evolutionary computation conference (GECCO), Seattle, Washington, USA, pp 1681-1688
42. Gomez F, Miikkulainen R (1998) 2-D pole balancing with recurrent evolutionary networks. In: Proceedings of the international conference on artificial neural networks (ICANN). Skovde, Sweden. Elsevier, New York
43. Goldberg DE, Richardson J (1987) Genetic algorithms with sharing for multimodal function optimization. In: Proceedings of the second international conference on genetic algorithms. Lawrence Erlbaum Associates, Hillsdale, pp 41-49
44. Gruau F, Whitley D, Pyeatt L (1996) A comparison between cellular encoding and direct encoding for genetic neural networks. Technical Report NC-TR-96-048, NeuroCOLT
45. Gomez F, Miikkulainen R (1999) Solving non-Markovian control tasks with neuroevolution. In: Proceedings of the 16th international joint conference on artificial intelligence. Morgan Kaufmann, Denver
46. Coons KE, Robatmili B, Taylor ME, Maher BA, Burger D, McKinley KS (2008) Feature selection and policy optimization for distributed instruction placement using reinforcement learning. In: Proceedings of the 7th international joint conference on parallel architectures and compilation techniques (PACT), Toronto, Ontario, Canada
47. Skalak DB (1994) Prototype and feature selection by sampling and random mutation hill-climbing algorithms. In: Proceedings of the 11th international conference on machine learning. Morgan Kaufmann, New Brunswick, pp 293-301
48. Mayr C (2003) NEAT Matlab. Available via http://www.cs.utexas.edu/*nn/soft-view.php?SoftID=23. Accessed 4 Sept 2008
49. Ethembabaoglu A, Whiteson S (2008) Automatic feature selection using FS-NEAT. Technical report IAS-UVA-08-02, Intelligent Autonomous Systems Group, University of Amsterdam