Result 1 to 20 of 47 total
Accepting the natural order of rules in a logic program with preferences. (English)
Gallagher, John P. (ed.) et al., Technical communications of the 27th international conference on logic programming (ICLP 2011), Lexington, Kentucky, USA, July 6‒10, 2011. Wadern: Schloss Dagstuhl ‒ Leibniz Zentrum für Informatik (ISBN 978-3-939897-31-6). LIPICS ‒ Leibniz International Proceedings in Informatics 11, 284-289, electronic only (2011).
1
Decision making with multiple objectives using GAI networks. (English)
Artif. Intell. 175, No. 7-8, 1153-1179 (2011).
2
The local geometry of multiattribute tradeoff preferences. (English)
Artif. Intell. 175, No. 7-8, 1122-1152 (2011).
3
Preferences in AI: an overview. (English)
Artif. Intell. 175, No. 7-8, 1037-1052 (2011).
4
Compactly representing utility functions using weighted goals and the Max aggregator. (English)
Artif. Intell. 174, No. 15, 1222-1246 (2010).
5
Updating action domain descriptions. (English)
Artif. Intell. 174, No. 15, 1172-1221 (2010).
6
Matrix representation and extension of coalition analysis in group decision support. (English)
Comput. Math. Appl. 60, No. 5, 1164-1176 (2010).
7
Preference aggregation for group decision making with multiple criteria. (Chinese)
Math. Pract. Theory 39, No. 6, 121-126 (2009).
8
Dependencies between players in Boolean games. (English)
Int. J. Approx. Reasoning 50, No. 6, 899-914 (2009).
9
Measurement-theoretic foundation of preference-based dyadic deontic logic. (English)
He, Xiangdong (ed.) et al., Logic, rationality, and interaction. Second international workshop, LORI 2009, Chongqing, China, October 8‒11, 2009. Proceedings. Berlin: Springer (ISBN 978-3-642-04892-0/pbk). Lecture Notes in Computer Science 5834. Lecture Notes in Artificial Intelligence, 278-291 (2009).
10
Representing utility functions via weighted goals. (English)
Math. Log. Q. 55, No. 4, 341-361 (2009).
11
Fuzzy Arrow’s theorem. (English)
New Math. Nat. Comput. 5, No. 2, 371-383 (2009).
12
Multi-party and multi-attribute negotiation support system based on preference representation of artificial psychology. (Chinese)
J. Comput. Appl. 28, No. 5, 1272-1275 (2008).
13
Multiagent resource allocation in $k$-additive domains: preference representation and complexity. (English)
Ann. Oper. Res. 163, 49-62 (2008).
14
On an approach to the realization of fuzzy databases. (Ukrainian)
Visn., Ser. Fiz.-Mat. Nauky, Kyïv. Univ. Im. Tarasa Shevchenka 2008, No. 2, 83-87 (2008).
15
An algorithmic approach to preference representation. (English)
Int. J. Uncertain. Fuzziness Knowl.-Based Syst. 16, Suppl. 2, 1-18 (2008).
16
Logical formalisms for representing bipolar preferences. (English)
Int. J. Intell. Syst. 23, No. 9, 985-997 (2008).
17
Local relational string and mutual matching for image retrieval. (English)
Inf. Process. Manage. 44, No. 3, 1201-1213 (2008).
18
The role of fuzziness in decision making. (English)
Wang, Paul P. (ed.) et al., Fuzzy logic. A spectrum of theoretical and practical issues. Berlin: Springer (ISBN 978-3-540-71257-2/hbk). Studies in Fuzziness and Soft Computing 215, 337-349 (2007).
19
A knowledge-based approach for selecting information sources. (English)
Theory Pract. Log. Program. 7, No. 3, 249-300 (2007).
20
Result 1 to 20 of 47 total
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