A prolog based system that assists experts to construct and simulate fuzzy cognitive maps

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5138 LNAI, Issue , 2008, Pages 288-300

  Tsadiras, Athanasios ^a  

^a ALEXANDER TECHNOLOGICAL EDUCATIONAL INSTITUTE OF THESSALONIKI   (Greece)

Author keywords

Decision making; Fuzzy Cognitive Maps; Predictions; Prolog; Simulation

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONFORMAL MAPPING; FORECASTING; FUZZY NEURAL NETWORKS; FUZZY RULES; FUZZY SYSTEMS; LARGE SCALE SYSTEMS; MAPS; NEURAL NETWORKS; OPTICAL PROJECTORS; PLANNING; PROBLEM SOLVING; STRATEGIC PLANNING;

A PROLOGS; ARTIFICIAL NEURAL NETWORKS; COMPUTER SKILLS; DECISION MAKERS; FUZZY COGNITIVE MAPS; PREDICTIONS; PROLOG; SIMULATION;

FUZZY LOGIC;

EID: 55349110665     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87881-0_26     Document Type: Conference Paper

References (25)

1. Billman, B., Courtney, J.F.: Automated Discovery in Managerial Problem Formulation: Formation of Causal Hypotheses for Cognitive Mapping. Decision Sciences 24, 23-41 (1993)
2. Bougon, M.G.: Congregate Cognitive Maps: A Unified Dynamic Theory of Organization and Strategy. Journal of Management Studies 29, 369-389 (1992)
3. Çoban, O., Seçme, G.: Prediction of socio-economical consequences of privatization at the firm level with fuzzy cognitive mapping. Information Sciences: an International Journal 169(1-2), 131-154 (2005)
4. Papageorgiou, E., Groumpos, P.: A Weight Adaptation Method for Fuzzy Cognitive Maps to a Process Control Problem. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3037, pp. 515-522. Springer, Heidelberg (2004)
5. John, R.I., Innocent, P.R.: Modeling uncertainty in clinical diagnosis using fuzzy logic. IEEE Transactions on Systems, Man and Cybernetics 35(6), 1340-1350 (2005)
6. Andreou, A.S., Mateou, N.H., Zombanakis, G.A.: The Cyprus Puzzle And The Greek Turkish Arms Race: Forecasting Developments Using Genetically Evolved Fuzzy Cognitive Maps. Defence and Peace Economics 14(4), 293-310 (2003)
7. Tsadiras, A.K., Kouskouvelis, I., Margaritis, K.G.: Using Fuzzy Cognitive Maps as a Decision Support System for Political Decisions. In: Manolopoulos, Y., Evripidou, S., Kakas, A.C. (eds.) PCI 2001. LNCS, vol. 2563, pp. 172-182. Springer, Heidelberg (2003)
8. Ramsey, D., Veltman, C.: Predicting the effects of perturbations on ecological communities: what can qualitative models offer? Journal of Animal Ecology 74, 905-916 (2005)
9. Hobbs, B.F., Ludsin, S., Knight, R.L., Ryan, P.A., Biberhofer, J.: Fuzzy Cognitive Mapping as a Tool to Define Management Objectives for Complex Ecosystems. Ecological Applications 12(5) (October 2002)
10. Axelrod, R.: Structure of Design. Princeton University Press, Princeton (1976)
11. Kosko, B.: Fuzzy Cognitive Maps. Inter. Jour, of Man-Machine Studies 24, 65-75 (1986)
12. Kosko, B.: Neural Networks and Fuzzy Systems. Prentice-Hall, Englewood Cliffs (1992)
13. Khan, M.S., Chong, A., Gedeon, T.: A Methodology for Developing Adaptive Fuzzy Cognitive Maps for Decision Support. Journal of Advanced Computational Intelligence 4(6), 403-407 (2000)
14. Khan, M.S., Quaddus, M.: Group Decision Support Using Fuzzy Cognitive Maps for Causal Reasoning. Group Decision and Negotiation 13, 463-480 (2004)
15. Tsadiras, A.K., Margaritis, K.G.: Cognitive Mapping and Certainty Neuron Fuzzy Cognitive Maps. Information Sciences 101, 109-130 (1997)
16. Taber, R., Yager, R.R., Helgason, C.M.: Quantization effects on the equilibrium behavior of combined fuzzy cognitive maps. International Journal of Intelligent Systems 22(2), 181-202 (2006)
17. Stach, W., Kurgan, L., Pedrycz, W., Reformat, M.: Genetic learning of fuzzy cognitive maps. Fuzzy Sets and Systems 153(3), 371-401 (2005)
18. Eberhart, R.C., Dobbins, R.W.: Neural Network PC Tools. Academic Press, London (1990)
19. Tsadiras, A.K., Margaritis, K.G.: Recursive Certainty Neurons and an Experimental Study of their Dynamical Behaviour. In: Proceedings of the European Congress on Intelligent Techniques and Soft Computing (EUFIT 1997), Aachen, Germany, September 1997, pp. 510-515 (1997)
20. Buchanan, B.G., Shortliffe, E.H.: Rule-Based Expert Systems. The MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley, Reading (1984)
21. Bratko, I.: Prolog-Programming for Artificial Intelligence, 3rd edn. Addison Wesley, Reading (2000)
22. Sharp, R.: CAT2: An Experimental Eurotra Alternative. Machine Translation 6, 215-228 (1991)
23. Aho, V., Sethi, R., Ullman, J.D.: Compilers: Principles, Techniques and Tools. AddisonWesley, Reading (1986)
24. Tsadiras, A.K., Margaritis, K.G.: An Experimental Study of Dynamics of the Certainty Neuron Fuzzy Cognitive Maps. NeuroComputing 24, 95-116 (1999)
25. SWI-Prolog, Free Software Prolog environment, licensed under the Lesser GNU Public License, http://www.swi-prolog.org