Adaptive Decision-Making by Systems of Cooperating Intelligent Agents Organized on Rough Mereological Principles

Intelligent Automation and Soft Computing

Volumn 2, Issue 2, 1996, Pages 121-132

  Polkowski, Lech ^a   Skowron, Andrzej ^a  

^a UNIVERSITY OF WARSAW   (Poland)

Author keywords

Adaptative decision making; Adaptive systems; Approximate reasoning; Cooperative multi agent systems; Distributed AI; Reasoning under uncertainty; Rough mereology; Rough sets

Indexed keywords

EID: 0041549720     PISSN: 10798587     EISSN: 2326005X     Source Type: Journal    
DOI: 10.1080/10798587.1996.10750661     Document Type: Article

References (22)

1. Amarel, S. PANEL on AI and Design. IJCA1-91. San Mateo, Morgan Kaufmann (1991), pp. 563-565.
2. Brown, E. M. Boolean Reasoning. Dordrecht, Kluwer, 1990.
3. Bums, M. Resources: Automated Fabrication. Improving Productivity in Manufacturing. Englewood Cliffs. NJ. Prentice Hall, 1993.
4. Connolly, J. H., and E. A. Edmunds. CSCW and Artificial Intelligence. Berlin-Heidelbcrg, Springer Verlag, 1994.
5. Davis, R., and R. G. Smith. Negotiations as a metaphor for distributed problem solving. '' Artificial Intelligence, Vol. 20 (1989), pp. 63-109.
6. Durfee, E. H. Coordination of Distributed Problem Solvers. Boston, Kluwer, 1988.
7. Ephrati, E., and J. S. Rosenschein. Divide and Conquer in Multi-agent Planning. AAAI-1994, Menlo-Park, CA, AAAI Press/MIT Press (1994), pp. 375-380.
8. Ishida, T. Parallel. Distributed and Multiagent Production Systems. LNCS 878, Berlin-Heidelberg. Springer Verlag, 1994.
9. LeSniewski, S. Foundations of the general theory of sets. Surma. Srzednicki, Barnett. Rickey (eds.), Stanislaw LeSniewski, Collected Works, Dordrecht. Kluwer (1992), pp. 128-173.
10. Mamdani, E. H., and S. Assiiian. An experimeni in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies, Vol. 7 (1975), pp. 1-13.
11. Pawlak, Z. Rough sets: Theoretical aspects of reasoning about data. Dordrecht, Kluwer, 1991.
12. Pao, Y. H. Adaptive Pattern Recognition and Neural Networks. Reading, MA, Addison Wesley. 1989.
13. Payne, J. W., J. R. Bcttman, and E. J. Johnson. The Adaptive Decision Maker. Cambridge, CUP, 1993.
14. Polkowski, L., and A. Skowron. Rough mereology. ISMIS-94. Lecture Notes in Artificial Intelligence. Vol. 869. Berlin, Springer-Verlag (1994), pp. 85-94.
15. Polkowski, L., and A Skowron. Logic of rough inclusion. Rough mereological functions. Rough functions. ICS Research Report 12/94. Institute of Computer Sci., Warsaw University of Technology, 1994.
16. Polkowski, L., A. Skowron, and J. Zytkow. Tolerance based rough sets. Conference Proceedings RSSC'94: The Third International Workshop on Rough Sets and Soft Computing. San Jose State University, CA, November 10-12 (1994), pp. 142-149.
17. Rao, R. B., and S. C.-Y. Lu. Building models to support synthesis in early stage product design. AAAI-93, Menlo Park, AAAI Press/MIT Press (1993), pp. 277-282.
18. Skowron, A., Synthesis of adaptive decision systems from experimental data. Proc. of the Fifth Scandinavian Conference on Artificial Intelligence SCAI-95, Aamadt, A., Komorowski, J. (eds.), Amsterdam, IOS Press (1995), pp. 220-238.
19. Sriram, D., R. Logcher, and S. Fukuda. Computer-Aided Cooperative Product Development, LNCS, Vol. 492, Berlin, Springer-Verlag, 1991.
20. Wegener, I. The Complexity of Boolean Functions. New York, Wiley, 1987.
21. Zadeh, L. Fuzzy sets. Dubois, D., Prade, H., Yager, R. R. (eds), Readings in Fuzzy Sets for Intelligent Systems, San Mateo, Morgan Kauffmann, 1993.
22. Zlotkin, G., and J. Rosenshein. Incomplete information and deception in multi-agent negotiations. IJCA/-91, San Mateo, Morgan Kaufmann (1991), pp. 225-231.