Tractable fragments of fuzzy qualitative algebra

Spatial Cognition and Computation

Volumn 8, Issue 1-2, 2008, Pages 150-166

  Badaloni, Silvana ^a   Falda, Marco ^a   Giacomin, Massimiliano ^b  

^a UNIVERSITY OF PADOVA   (Italy)

^b UNIVERSITY OF BRESCIA   (Italy)

Author keywords

Possibility theory; Qualitative algebras; Temporal reasoning

Indexed keywords

FUZZY ALGEBRA; FUZZY CSPS; GENERAL METHODOLOGIES; POSSIBILITY THEORY; TEMPORAL CONSTRAINTS; TEMPORAL REASONING; VAGUENESS AND UNCERTAINTY;

CONSTRAINT SATISFACTION PROBLEMS; UNCERTAINTY ANALYSIS;

ALGEBRA;

EID: 77951445860     PISSN: 13875868     EISSN: 15427633     Source Type: Journal    
DOI: 10.1080/13875860801944812     Document Type: Article

References (19)

1. Allen, J. F. (1983). Maintaining knowledge about temporal intervals. Com-munications of the ACM, 26(1), 832-843.
2. Allen, J. F. (1995). Natural language understanding (2nd Ed.). Benjamin/ Cummings.
3. Badaloni, S., Falda, M., & Giacomin, M. (2003). Integrating qualitative and quantitative constraints in fuzzy temporal networks. In Proc. of the workshop on spatial and temporal reasoning (pp. 105-112).
4. Badaloni, S., Falda, M., & Giacomin, M. (2004). Integrating quantitative and qualitative constraints in fuzzy temporal networks. AI Communications, 17(4), 183-272.
5. Badaloni, S., Falda, M., & Giacomin, M. (2007). Fuzzy extensions of qualitative algebra tractable fragments. In Proc. of the workshop on spatial and temporal reasoning (pp. 11-15).
6. Badaloni, S., & Giacomin, M. (2006). The algebra IAfuz: A framework for qualitative fuzzy temporal reasoning. Artificial Intelligence, 170(10), 872-908.
7. Dechter, R., Meiri, I., & Pearl, J. (1991). Temporal constraint networks. Artificial Intelligence, 49, 61-95.
8. Dubois, D., Fargier, H., & Prade, H. (1996). Possibility theory in constraint satisfaction problems: Handling priority, preference and uncertainty. Ap-plied Intelligence, 6, 287-309.
9. Giacomin, M. (2001). From crisp to fuzzy constraint networks. In Proc. of CP'01 Workshop Modelling and Solving Problems with Soft Constraints.
10. Jonsson, P., Drakengren, T., & Backström, C. (1999). Computational complexity of relating time points with intervals. Artificial Intelligence, 109, 273-295.
11. Jonsson, P., & Krokhin, A. (2004). Complexity classification in qualitative temporal constraint reasoning. Artificial Intelligence, 160, 35-51.
12. Krokhin, A., Jeavons, P., & Jonsson, P. (2001). Reasoning about temporal relations: The tractable subalgebras of Allen's interval algebra (Tech. Rep. No. PRG-RR-01-12). Oxford University.
13. Meiri, I. (1996). Combining qualitative and quantitative constraints in temporal reasoning. Artificial Intelligence, 87, 343-385.
14. Nebel, B., & Bürckert, H. J. (1995). Reasoning about temporal relations: A maximal tractable subclass of Allen's interval algebra. Journal of the ACM, 42(1), 43-66.
15. Rendell, D., Cui, Z., & Cohn, A. (1992). A spatial logic based on regions and connections. In 3rd International Conference on Knowledge Representa-tion and Reasoning (pp. 165-176). San Mateo, CA: Morgan Kaufmann.
16. Renz, J. (1999). Maximal tractable fragments of the region connection calculus: A complete analysis. Artificial Intelligence, 108, 69-123.
17. van Beek, P., & Cohen, R. (1990). Exact and approximate reasoning about temporal relations. Computational Intelligence, 6, 132-144.
18. Vilain, M., Kautz, H., & van Beek, P. (1989). Constraint propagation algorithms for temporal reasoning: A revised report. In J. de Kleer and D. S. Weld (Eds.), Readings in qualitative reasoning about physical systems (pp. 373-381). San Mateo, CA: Morgan Kaufmann.
19. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338-353.