User-Centric Evolutionary Computing: Melding Human and Machine Capability to Satisfy Multiple Criteria

Natural Computing Series

Volumn , Issue , 2008, Pages 263-283

  Parmee, Ian C ^a   Abraham, Johnson A R ^b   Machwe, Azahar ^a  

^a UNIVERSITY OF THE WEST OF ENGLAND   (United Kingdom)

^b Level E Limited   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 74349098746     PISSN: 16197127     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-72964-8_13     Document Type: Chapter

References (31)

1. Abraham, J. A. R. and Parmee, I. C. (2004) Extraction of emerging multiobjective design information from COGA data, Procs. of Adaptive Computing in Design and Manufacture VI, Springer, London.
2. Avigad, G., Moshaiov, A. and Brauner, N. (2004) Concept-based interactive brainstorming in engineering design. J. of Advanced Computational Intelligence and Intelligent Informatics, 8(5).
3. Bentley, P. J. (2000) Exploring Component-Based Representations-The Secret of Creativity by Evolution? In Proc. of the Fourth International Conference on Adaptive Computing in Design and Manufacture (ACDM 2000), I. C. Parmee (ed), University of Plymouth, UK. pp. 161–172.
4. Bonham, C. R. and Parmee, I. C. (1999) An investigation of exploration and exploitation in cluster-oriented genetic algorithms. Procs. of the Genetic and Evolutionary Computation Conference, Orlando, Florida, USA: 1491–1497.
5. Carnahan, B. and Dorris, N. (2004) Identifying relevant symbol design criteria using interactive evolutionary computation, Procs. Genetic and Evolutionary Computing Conference (GECCO), Seattle, USA.
6. Cvetkovic, D. and Parmee, I. C. (2003) Agent-based support within an interactive evolutionary design system. J. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Cambridge University Press, 16(5): 331– 342
7. Cvetkovic, D. and Parmee, I. C. (2001) Preferences and their Application in Evolutionary Multi-objective Optimisation. IEEE Transactions on Evolutionary Computation, 6(1):42–57.
8. Gero J. S., Louis S. J., Kundu, S. (1994) Evolutionary learning of novel grammars for design improvement. J. Artificial Intelligence for Design, Analysis and Manufacture, 8: 83–94.
9. Gero J. S., Shi X. G., (1999) Design development based on an analogy with developmental biology. CAADRIA ’99, J. Gu and Z. Wei (eds), Shanghai, China: 253–264.
10. Gero, J. S. (2002) Computational models of creative designing based on situated cognition, in T Hewett and T Kavanagh (eds), Creativity and Cognition, New York, ACM Press, USA.
11. Goel, A. K. (1997) Design, analogy and creativity. IEEE Expert, Intelligent Systems and their Applications, 12(3): 62–70.
12. Grierson, D. E., Khajehpour, S. (2002) Method for Conceptual Design Applied to Office Buildings. Journal of Computing in Civil Engineering, 16 (2) pp. 83– 103.
13. Inselberg, A. (1985) The plane with parallel coordinates, The Visual Computer, 1: 69–91.
14. Kim, H. S., Cho, S. B. (2005) Fashion design using interactive genetic algorithm with knowledge-based encoding. In: Y. Jin (Ed), Knowledge Incorporation in Evolutionary Computation, Springer Verlag.
15. Machwe, A., Parmee, I. C., Miles, J. C. (2005a) Overcoming representation issues when including aesthetic criteria in evolutionary design. Procs. ASCE Int. Conf. on Computing in Civil Engineering, Cancun, Mexico.
16. Machwe, A., Parmee, I. C. and Miles, J. C. (2005b) Integrating Aesthetic Criteria with a user-centric evolutionary system via a component-based design representation. Proceedings of International Conference on Engineering Design, Melbourne, Australia.
17. Machwe, A. and Parmee, I. C. (2006a) Introducing machine learning within an interactive evolutionary design environment. Procs. Design 2006, Croatia.
18. Machwe, A. and Parmee, I. C. (2006b) Integrating aesthetic criteria with evolutionary processes in complex, free-form design — an initial investigation. Procs. IEEE Congress on Evolutionary Computation, Vancouver, Canada.
19. Parmee, I. C. (1996). The maintenance of search diversity for effective design space decomposition using cluster oriented genetic algorithms (COGAs) and multi-agent strategies (GAANT). Procs. 2nd International Conference on Adaptive Computing in Engineering Design and Control, Plymouth, UK; pp 128–138.
20. Parmee, I. C. (2001) Evolutionary and adaptive computing in engineering design. Springer Verlag, London.
21. Parmee, I. C. (2002) Improving problem definition through interactive evolutionary computation. J. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 16 (3), Cambridge University Press: 185–202.
22. Parmee, I. C. (2004) User-centric evolutionary design. Procs. Design 2004, Dubrovnic.
23. Parmee, I. C., Abraham, J. A. R. (2005) Interactive Evolutionary Design. In: Y. Jin (Ed), Knowledge Incorporation in Evolutionary Computation, Springer Verlag.
24. Parmee I. C., Abraham J. A. R. (2004) Supporting Implicit Learning via the Visualisation of COGA Multi-objective Data. Procs. IEEE Congress on Evolutionary Computation 2004, Portland: 395–402.
25. Parmee, I. C., Bonham, C. R. (1999) Towards the support of innovative conceptual design through interactive designer/evolutionary computing strategies. J. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Cambridge University Press, 14: 3–16.
26. Parmee, I. C., Watson, A. W. (1999) Preliminary Airframe Design using Coevolutionary Multi-objective Genetic Algorithms. Proceedings of the Genetic and Evolutionary Computation Conference, Orlando, Florida, USA:1651–1665.
27. Parmee, I., Watson, A., Cvetkovic, D., Bonham, C. R. (2000) Multi-objective Satisfaction within an Interactive Evolutionary Design Environment. Journal of Evolutionary Computation; MIT Press; 8(2): 197–222.
28. Rosenman, M. A. (1997) An exploration into evolutionary models fornon-routine design,Artificial Intelligence in Engineering, 11(3):287–293.
29. Su N. P. (1990) The principles of design. Oxford University Press, New York.
30. Takagi, H., Ohsaki, M. (1999) IEC-based Hearing Aid Fitting. Procs. International Conference on System, Man and Cybernetics (SMC ’99),IEEE, Vol 3, 657–662.
31. Zitzler, E., Laumanns, M., Thiele, L. (2002) SPEA2: Improving the Strength Pareto Evolutionary Algorithm for Multiobjective Optimization. Procs. Evolutionary Methods for Design, Optimisation, and Control, CIMNE, Barcelona: 95–100.