Incorporating domain-specific knowledge into a genetic algorithm to implement case-based reasoning adaptation

Knowledge-Based Systems

Volumn 19, Issue 3, 2006, Pages 192-201

  Passone, S ^a   Chung, P W H ^b   Nassehi, V ^b  

^a Massachusetts Institute of Technology Cambridge   (United States)

^b LOUGHBOROUGH UNIVERSITY   (United Kingdom)

Author keywords

Case adaptation; Case based reasoning system; Genetic algorithm

Indexed keywords

FORMAL LOGIC; GENETIC ALGORITHMS; KNOWLEDGE ACQUISITION; MATHEMATICAL MODELS; PROBLEM SOLVING;

ALGORITHM-BASED ADAPTATION; CASE ADAPTATION; CASE-BASED REASONING SYSTEMS; DOMAIN-SPECIFIC KNOWLEDGE;

KNOWLEDGE BASED SYSTEMS;

EID: 33745020205     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2005.07.007     Document Type: Article

References (14)

1. Hanney K., and Keane M.T. The adaptation knowledge: how to easy it by learning from cases. Proceedings of the Second International Conference on Case-Based Reasoning (1997), Springer, Berlin pp. 359-370
2. Kolodner J. Case-Based Reasoning (1993), Morgan Kaufmann, San Mateo, CA
3. Leake D.B., Kinley A., and Wilson D. Acquiring case adaptation knowledge: a hybrid approach. Proceedings of the Thirteenth National Conference on Artificial Intelligence (1996), AAAI Press, Menlo Park, CA
4. Jarmulak J., Craw S., and Rowe R. Using case-base data to learn adaptation knowledge for design. Proceedings of the Seventeenth IJCAI Conference (2001), Morgan Kaufmann, San Mateo, CA pp. 1011-1016
5. W. Wilke, I. Vollrath, K.D. Althoff, R. Bergmann, A framework for learning adaptation knowledge based on knowledge light approaches, Proceedings of the Fifth German Workshop on Case-Based Reasoning, 1997.
6. McDowell D.M., and O'Connor B.A. Hydraulic Behaviour of Estuaries (1977), Macmillan, London
7. Thompson G. Mathematical-models and engineering design. Journal of the Institution of Water and Environmental Management 7 (1993) 18-23
8. French J.R., and Clifford N.J. Hydrodynamic modelling as a basis for explaining estuarine environmental dynamics: some computational and methological issues. Hydrological Process 14 (2000) 2089-2108
9. Goldberg D.E. Genetic Algorithm in Search, Optimisation and Machine Learning (1989), Addison-Wesley, Reading, MA
10. Louis S.J., and Johnson J. Solving similar problems using genetic algorithms and case-base memory. Proceedings of the Seventh International Conference on Genetic Algorithms (1997), Morgan Kauffman, San Mateo, CA pp.101-127
11. Babovic V., Wu Z., and Larsen L.C. Calibrating hydrodynamics models by means of simulated evolution. Proceedings of the First International Conference in Hydroinformatics (1994), Balkema, Amsterdam pp. 193-200
12. J.H. Bikangaga, Mathematical modelling of the hydrodynamics and transport of soluble reactive pollutants in Narrow Tidal Rivers, PhD Thesis, 1993.
13. Passone S., Chung P.W.H., and Nassehi V. Case-based reasoning for estuarine model design. Proceedings of the Sixth European Conference on Case-Based Reasoning (2002), Springer, Berlin pp. 590-603
14. Bikangaga J.H., and Nassehi V. Application of computer modelling techniques to the determination of optimum effluent discharge policies in Tidal water systems. Water Resources 29 10 (1995) 2367-2375