Novelty-based multiobjectivization

Studies in Computational Intelligence

Volumn 341, Issue , 2011, Pages 139-154

  Mouret, Jean Baptiste ^a  

^a SORBONNE UNIVERSITÉ   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 79952168756     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-18272-3_10     Document Type: Conference Paper

References (25)

1. Abbass, H.A., Deb, K.: Searching under multi-evolutionary pressures. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Deb, K., Thiele, L. (eds.) EMO 2003. LNCS, vol. 2632, pp. 391-404. Springer, Heidelberg (2003)
2. Bentley, J.L.:Multidimensional binary search trees used for associative searching. Communication of the ACM 18(9), 509-517 (1975)
3. Bui, L., Abbass, H.A., Branke, J.: Multiobjective optimization for dynamic environments. Proceedings of the IEEE-CEC 3, 2349-2356 (2005) (Pubitemid 41496141)
4. Deb, K.: Multi-objectives optimization using evolutionnary algorithms. Wiley, Chichester (2001)
5. Deb, K., Agrawal, S., Pratap, A., Meyarivan, T.: A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Proceedings of PPSN VI, pp. 849-858 (2000)
6. Doncieux, S.,Mouret, J.B.: Single step evolution of robot controllers for sequential tasks. In: Proceedings of GECCO 2009, ACM, New York (2009)
7. Fonseca, C.M., Fleming, P.J.: Genetic algorithms for multiobjective optimization: formulation, discussion and generalization. In: Proceedings of the Fourth International Conference on Evolutionary Programming, pp. 416-423 (1993)
8. Goldberg, D.E., Richardson, J.: Genetic algorithms with sharing for multimodal function optimization. In: Proceedings of the Second International Conference on Genetic Algorithms, pp. 148-154. Morgan Kaufmann, San Francisco (1987)
9. Gomez, F.: Sustaining diversity using behavioral information distance. In: Proceedings of GECCO 2009 (2009)
10. Greiner, D., Emperador, J.,Winter, G., Galván, B.: Improving Computational Mechanics Optimum Design Using Helper Objectives: An Application in Frame Bar Structures. In: Obayashi, S., Deb, K., Poloni, C., Hiroyasu, T., Murata, T. (eds.) EMO 2007. LNCS, vol. 4403, pp. 575-589. Springer, Heidelberg (2007) (Pubitemid 350270912)
11. Handl, J., Lovell, S.C., Knowles, J.: Multiobjectivization by decomposition of scalar cost functions. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol. 5199, pp. 31-40. Springer, Heidelberg (2008)
12. de Jong, E.D.,Watson, R.A., Pollack, J.B.: Reducing bloat and promoting diversity using multi-objective methods. In: Proceedings of GECCO 2001, pp. 11-18 (2001)
13. Knowles, J.D., Watson, R.A., Corne, D.W.: Reducing Local Optima in Single-Objective Problems by Multi-objectivization. In: Zitzler, E., Deb, K., Thiele, L., Coello Coello, C.A., Corne, D.W. (eds.) EMO 2001. LNCS, vol. 1993, pp. 268-282. Springer, Heidelberg (2001)
14. Lehman, J., Stanley, K.: Exploiting open-endedness to solve problems through the search for novelty. In: Proceedings of Artificial Life XI, pp. 329-336 (2008)
15. Mouret, J.B., Doncieux, S.: Incremental Evolution of Animats Behaviors as a Multiobjective Optimization. In: Asada, M., Hallam, J.C.T., Meyer, J.-A., Tani, J. (eds.) SAB 2008. LNCS (LNAI), vol. 5040, pp. 210-219. Springer, Heidelberg (2008)
16. Mouret, J.B., Doncieux, S.: Evolving modular neural-networks through exaptation. In: Proceedings of IEEE Congress on Evolutionary Computation, IEEE-CEC (2009)
17. Mouret, J.B., Doncieux, S.: Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity. In: Proceedings of IEEE-CEC (2009)
18. Mouret, J.B., Doncieux, S.: Using behavioral exploration objectives to solve deceptive problems in neuro-evolution. In: Proceedings of GECCO (2009)
19. Praditwong, K., Yao, X.: How well do multi-objective evolutionary algorithms scale to large problems. In: Proceedings of IEEE-CEC, pp. 3959-3966 (2007)
20. Purshouse, R.C., Fleming, P.J.: On the Evolutionary Optimization of Many Conflicting Objectives. IEEE Transactions on Evolutionary Computation 11(6), 770-784 (2007) (Pubitemid 350187490)
21. Risi, S., Vanderbleek, S.D., Hughes, C.E., Stanley, K.O.: How novelty search escapes the deceptive trap of learning to learn. In: Proceedings of GECCO (2009)
22. Stanley, K.O., Miikkulainen, R.: Evolving neural networks through augmenting topologies. Evolutionary Computation 102(2), 99-127 (2002)
23. Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)
24. Toffolo, A., Benini, E.: Genetic diversity as an objective in multi-objective evolutionary algorithms. Evolutionary Computation 11(2), 151-167 (2003) (Pubitemid 37044183)
25. Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: Improving the Strength Pareto Evolutionary Algorithm. In: Evolutionary Methods for Design, Optimisation and Control with Application to Industrial Problems (EUROGEN 2001), pp. 95-100 (2001)