Evolutionary design of emergent behavior

Understanding Complex Systems

Volumn 2008, Issue , 2008, Pages 123-140

  Branke, Jürgen ^a   Schmeck, Hartmut ^a  

^a UNIVERSITY OF KARLSRUHE   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 54849442272     PISSN: 18600832     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-77657-4_6     Document Type: Article

References (75)

1. E. Aarts and J. Korst. Simulated annealing and Boltzmann machines. Wiley, 1989.
2. A. N. Aizawa and B. W. Wah. Scheduling of genetic algorithms in a noisy environment. Evolutionary Computation, pages 97-122, 1994.
3. E. Alba and M. Tomassini. Parallelism and evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 6(5):443-461, 2002.
4. L. A. Albert and D. E. Goldberg. Efficient evaluation genetic algorithms under integrated fitness functions. Technical Report 2001024, Illinois Genetic Algorithms Laboratory, Urbana-Champaign, USA, 2001.
5. C. Anderson. Creation of desirable complexity: Strategies for designing self-organized systems. In D. Braha et al., editors, Complex Engineered Systems, pages 101-121. Springer, 2006.
6. D. V. Arnold and H.-G. Beyer. Efficiency and mutation strength adaptation of the (μ/μi, λ)-ES in a noisy environment. In Schoenauer et al. [62], pages 39-48.
7. D. V. Arnold and H.-G. Beyer. Local performance of the (μ/μi, λ)-ES in a noisy environment. In W. Martin and W. Spears, editors, Foundations of Genetic Algorithms, pages 127-142. Morgan Kaufmann, 2000.
8. D. V. Arnold and H.-G. Beyer. A comparison of evolution strategies with other direct search methods in the presence of noise. Computational Optimization and Applications, 24:135-159, 2003.
9. C. Bernon, V. Camps, M.-P. Gleizes, and G. Picard. Tools for self-organizing applications engineering. In G. D. Serugendo et al., editors, Engineering Self-Organizing Systems, volume 2977 of LNAI, page 283.298. Springer, 2004.
10. H.-G. Beyer. Toward a theory of evolution strategies: Some asymptotical results from the (1 +, λ)-theory. Evolutionary Computation, 1(2):165-188, 1993.
11. J. Boesel. Search and Selection for Large-Scale Stochastic Optimization. PhD thesis, Northwestern University, Evanston, Illinois, USA, 1999.
12. E. Bonabeau, M. Dorigo, and G. Theraulaz. Swarm intelligence: From natural to artificial systems. Oxford University Press, 1999.
13. J. Branke. Creating robust solutions by means of an evolutionary algorithm. In A. E. Eiben, T. Bäck, M. Schoenauer, and H.-P. Schwefel, editors, Parallel Problem Solving from Nature, volume 1498 of LNCS, pages 119-128. Springer, 1998.
14. J. Branke. Evolutionary Optimization in Dynamic Environments. Kluwer, 2001.
15. J. Branke. Reducing the sampling variance when searching for robust solutions. In L. S. et al., editor, Genetic and Evolutionary Computation Conference (GECCO'01), pages 235-242. Morgan Kaufmann, 2001.
16. J. Branke, S. Chick, and C. Schmidt. Selecting a selection procedure. Technical report, Fontainebleau, 2005.
17. J. Branke and K. Deb. Integrating user preferences into evolutionary multiobjective optimization. In Y. Jin, editor, Knowledge Incorporation into Evolutionary Algorithms, pages 461-478. Springer, 2004.
18. J. Branke, K. Deb, H. Dierolf, and M. Osswald. Finding knees in multi-objective optimization. In Parallel Problem Solving from Nature number 3242 in LNCS, pages 722-731. Springer, 2004.
19. J. Branke, P. Funes, and F. Thiele. Evolving en-route caching strategies for the internet. In Genetic and Evolutionary Computation Conference volume 3103 of LNCS, pages 434-446. Springer, 2004.
20. J. Branke, A. Kamper, and H. Schmeck. Distribution of evolutionary algorithms in heterogeneous networks. In Genetic and Evolutionary Computation Conference, volume 3102 of LNCS, pages 923-934, 2004.
21. J. Branke, T. Kaußler, and H. Schmeck. Guidance in evolutionary multiobjective optimization. Advances in Engineering Software, 32(6):499-508, 2001.
22. J. Branke, M. Mnif, C. Müller-Schloer, H. Prothmann, U. Richter, F. Rochner, and H. Schmeck. Organic computing - addressing complexity by controlled self-organization. In International Symposium on Leveraging Applications of Formal Methods, Verification and Validation ACM, 2007.
23. J. Branke and C. Schmidt. Selection in the presence of noise. In E. Cantu-Paz, editor, Genetic and Evolutionary Computation Conference volume 2723 of LNCS, pages 766-777. Springer, 2003.
24. J. Branke and C. Schmidt. Sequential sampling in noisy environments. In X. Yao et al., editor, Parallel Problem Solving from Nature, volume 3242 of LNCS, pages 202-211. Springer, 2004.
25. J. Branke, C. Schmidt, and H. Schmeck. Efficient fitness estimation in noisy environments. In L. Spector et al., editors, Genetic and Evolutionary Computation Conference, pages 243-250. Morgan Kaufmann, 2001.
26. E. Cantu-Paz. Efficient and Accurate Parallel Genetic Algorithms. Kluwer, 2000.
27. I. Das. On characterizing the 'knee' of the pareto curve based on normal-boundary intersection. Structural Optimization, 18(2/ 3):107-115, 1999.
28. T. De Wolf and T. Holvoet. Emergence versus self-organization: Different concepts but promising when combined. In S. A. Brueckner et al., editors, Engineering Self-Organising Systems: Methodologies and Applications, number 3464 in LNCS, pages 1-15. Springer, 2005.
29. T. De Wolf and T. Holvoet. Towards a methodology for engineering self-organising emergent systems. In H. Czap et al., editors, Self-Organization and Autonomic Informatics, pages 18-34. Springer, 2005.
30. K. Deb. Solving goal programming problems using multi-objective genetic algorithms. In Congress on Evolutionary Computation, volume 1, pages 77-84. IEEE, 1999.
31. K. Deb. Multi-Objective Optimization using Evolutionary Algorithms Wiley, 2001.
32. K. A. DeJong. Evolutionary Computation. MIT Press, 2002.
33. R. C. Eberhart and Y. Shi. Swarm Intelligence. Morgan Kaufmann, 2001.
34. B. Edmonds. Using the experimental method to produce reliable self-organised systems. In S. Brueckner et al., editors, Engineering Self-Organising Systems, volume 3464 of LNAI, pages 84-99. Springer, 2005.
35. A. E. Eiben and J. E. Smith. Introduction to Evolutionary Computing Springer, 2003.
36. Repository on multi-objective evolutionary algorithms. online, http://www.lania.mx/$\sim$ccoello/EMOO/.
37. J. M. Fitzpatrick and J. J. Grefenstette. Genetic algorithms in noisy environments. Machine Learning, 3:101-120, 1988.
38. L. J. Fogel, A. J. Owens, and M. J. Walsh. Artificial Intelligence through Simulated Evolution. John Wiley, 1966.
39. M. C. Fu. Optimizationn for simulation: Theory vs. practice. INFORMS Journal of Computing, 14(3):192-215, 2002.
40. F. Glover. Tabu search - part I. ORSA Journal of Computing, 1(3):190-206, 1989.
41. P. Goldate. Optimierung einer Ampelsteuerung mit Hilfe von evolutionären Algorithmen. Master's thesis, Institute AIFB, University of Karlsruhe, 76128 Karlsruhe, Germany, August 2003.
42. D. E. Goldberg. Genetic Algorithms. Addison-Wesley, 1989.
43. A. Gosavi. Simulation-based optimization. Kluwer Academic, 2003.
44. H. Greiner. Robust optical coating design with evolutionary strategies. Applied Optics, 35(28):5477-5483, 1996.
45. U. Hammel and T. Bäck. Evolution strategies on noisy functions, how to improve convergence properties. In Y. Davidor, H. P. Schwefel, and R. Männer, editors, Parallel Problem Solving from Nature, volume 866 of LNCS. Springer, 1994.
46. J. Holland. Emergence - From chaos to order. Addison-Wesley, 1998.
47. Y. Jin. A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing, 9:3-12, 2005.
48. Y. Jin and J. Branke. Evolutionary optimization in uncertain environments - a survey. IEEE Transactions on Evolutionary Computation, 9(3):303-317, 2005.
49. S.-H. Kim and B. Nelson. A fully sequential procedure for indifference-zone selection in simulation. ACM Transactions on Modelin and Computer Simulation, 11(3):251-273, 2001.
50. J. R. Koza. Genetic Programming. MIT Press, 1991.
51. B. L. Miller. Noise, Sampling, and Efficient Genetic Algorithms. PhD thesis, Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1997. available as TR 97001.
52. B. L. Miller and D. E. Goldberg. Genetic algorithms, selection schemes, and the varying effects of noise. Evolutionary Computation, 4(2):113-131, 1996.
53. A. A. Minai, D. Braha, and Y. Bar-Yam. Complex engineered systems: A new paradigm. In D. Braha et al., editors, Complex Engineered Systems, pages 1-21. Springer, 2006.
54. R. Nagpal. A catalog of biologically-inspired primitives for engineering self-organization. In G. D. Serugendo et al., editors, Engineering Self-Organizing Systems, volume 2977 of LNAI, pages 53-62. Springer, 2004.
55. I. Paenke, J. Branke, and Y. Jin. Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation. IEEE Transactions on Evolutionary Computation, 10(4):405-420, 2006.
56. Parabon Inc. Company homepage. Online. http://www.parabon.com.
57. H. V. D. Parunak. "go to the ant" Engineering principles from natural multi-agent systems. Annals of Operations Research, 75:69-101, 1997.
58. I. Rechenberg. Evolutionsstrategie: Optimierung technischer Systeme nach Prinzipen der biologischen Evolution. Frommann-Holzboog, Stuttgart, 1973.
59. Y. Sano and H. Kita. Optimization of noisy fitness functions by means of genetic algorithms using history of search. In Schoenauer et al. [62], pages 571-580.
60. Y. Sano and H. Kita. Optimization of noisy fitness functions by means of genetic algorithms using history of search with test of estimation. In Congress on Evolutionary Computation, pages 360-365. IEEE Press, 2002.
61. H. Schmeck, U. Kohlmorgen, and J. Branke. Parallel implementations of evolutionary algorithms. In A. Zomaya, F. Ercal, and S. Olariu, editors, Solutions to Parallel and Distributed Computing Problems, pages 47-66. Wiley, 2000.
62. M. Schoenauer, K. Deb, G. Rudolph, X. Yao, E. Lutton, J. J. Merelo, and H.-P. Schwefel, editors. Parallel Problem Solving from Nature, volume 1917 of LNCS. Springer, 2000.
63. T. Schöler and C. Müller-Schloer. An observer/controller architecture for adaptive reconfigurable stacks. In M. Beigl and P. Lukowicz, editors, International Conference on Architecture Of Computing Systems, volume 3432 of LNCS, pages 139-153. Springer, 2005.
64. H.-P. Schwefel. Evolutionsstrategie und numerische Optimierung. PhD thesis, Technische Universität Berlin, Germany, 1975.
65. Setiηome. Project homepage. Online. http://setiathome.ssl.berkeley.edu/.
66. J. C. Spall. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 31:332-341, 1992.
67. J. C. Spall. Introduction to stochastic search and optimization. John Wiley and Sons, 2003.
68. P. Stagge. Averaging efficiently in the presence of noise. In A. E. Eiben, T. Bäck, M. Schoenauer, and H.-P. Schwefel, editors, Parallel Problem Solving from Nature V, volume 1498 of LNCS, pages 188-197. Springer, 1998.
69. X. Tang and S. T. Chanson. Coordinated en-route web caching. IEEE Transactions on Computers, 51(6):595-607, 2002.
70. J. Teich. Pareto-front exploration with uncertain objectives. In E. Zitzler, K. Deb, L. Thiele, C. A. C. Coello, and D. Corne, editors, Evolutionary Multi- Criterion Optimization, volume 1993 of LNCS pages 314-328. Springer, 2001.
71. A. Thompson. On the automatic design of robust elektronics through artificial evolution. In M. Sipper, D. Mange, and A. Peres-Urike, editors, International Conference on Evolvable Systems, pages 13 - 24. Springer, 1998.
72. D. S. Todd and P. Sen. Directed multiple objective search of design spaces using genetic algorithms and neural networks. In W. B. et al., editor, Genetic and Evolutionary Computation Conference, pages 1738-1743. Morgan Kaufmann, San Francisco, California, 1999.
73. S. Tsutsui and A. Ghosh. Genetic algorithms with a robust solution searching scheme. IEEE Transactions on Evolutionary Computation, 1(3):201-208, 1997.
74. United Devices. Company homepage. Online. http://www.ud.com.
75. D. Wiesmann, U. Hammel, and T. Bäck. Robust design of multilayer optical coatings by means of evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 2(4):162-167, 1998.