P. Giorgini, J. Mylopoulos, E. Nicchiarelli, and R. Sebastiani. Reasoning with Goal Models. In Proc. of ER'02, pp. 167--181, 2002. Home/Search Document Details and Download
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P. Giorgini, J. Mylopoulos, E. Nicchiarelli, and R. Sebastiani. Reasoning with Goal Models. In Proc. of ER'02, pp. 167--181, 2002.
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P. Giorgini, J. Mylopoulos, E. Nicchiarelli, and R. Sebastiani. Reasoning with Goal Models. In S. Spaccapietra, S. T. March, and Y. Kambayashi, editors, 21st International Conference on Conceptual Modeling (ER02), Tampere, Finland, volume 2503 of Lecture Notes in Computer Science. Springer-Verlag, 2002.
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P. Giorgini, E. Nicchiarelli, J. Mylopoulos, and R.Sebastiani. Reasoning with Goal Models. In Proc. Int. Conference of Conceptual Modeling -- ER'02, LNCS, Tampere, Finland, October 2002. Springer.
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P. Giorgini, J. Mylopoulos, E. Nicchiarelli, and R. Sebastiani. Reasoning with goal models. LNCS, 2503:167--??, 2002.
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P. Giorgini, J. Mylopoulos, E. Nicchiarelli, R. Sebastiani. "Reasoning with Goal Models ", in the Proceedings of the 21st International Conference on Conceptual Modeling (ER2002), Tampere, Finland, October 2002.
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P. Giorgini, E. Nicchiarelli, J. Mylopoulos, and R. Sebastiani. Reasoning with Goal Models. In Proc. Int. Conference of Conceptual Modeling -- ER'02, LNCS, Tampere, Finland, October 2002. Springer.
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....all contributions of the incoming relations. The algorithm terminates when an iteration adds no new values to any the variables of any node of the graph. The use of maximum value function guarantees the termination of the algorithm. Further details about this propagation algorithm are presented in [Gio02a]. 1 Initialize NODES 2 do 3 NODES NODES 4 foreach node n i 5 foreach incoming relation Aij 6 Dj ComputeD(Aij ) 7 Sj ComputeS(Aij) 8 ni.D Maxj(Dj) 9 ni.S Maxj(Sj) 10 while(NODESNODES ) Fig. 9. Basic propagation algorithm 5. Conclusions Modelers need to rely on patterns, ....
P. Giorgini, J. Mylopoulos, E. Nicchiarelli, and R. Sebastiani. Reasoning with Goal Models. In Proceedings of the 21 Intemational Conference on Conceptual Modeling (ER02), LNCS 2503 Springer Verlag. Tampere, Finland, October, 2002,
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....an attribute implies the satisfaction or denial of another goal. In Figure 11, for instance, the satisfaction of attribute Structure in 5 implies the satisfaction of attributes Reliability and Redundancy. The analysis for selecting an architecture is based on propagation algorithms presented in [23]. Basically, the idea is to assign a set of initial labels for some attributes of the graph, about their satisfiability and deniability, and see how this assignment leads to the labels propagation for other attributes. In particular, we adopt from [23] both qualitative and a numerical ....
....based on propagation algorithms presented in [23] Basically, the idea is to assign a set of initial labels for some attributes of the graph, about their satisfiability and deniability, and see how this assignment leads to the labels propagation for other attributes. In particular, we adopt from [23] both qualitative and a numerical axiomatization for goal (attributes) modeling primitives and label propagation algorithms that are shown to be sound and complete with respect to their respective axiomatization. In the following, a brief description of the qualitative algorithm. 31 To each ....
P. Giorgini, J. Mylopoulos, E. Nicchiarelli, and R. Sebastiani. Reasoning with goal models. In Proceedings of the 21st International Conference on Conceptual Modeling (ER 2002), Tampere, Finland, October 2002.
Multi-Agent Architectures as Organizational Structures - Giorgini, Kolp (2001) Self-citation (Giorgini Mylopoulos) (Correct)
....attribute implies the satisfaction or denial of another 30 goal. In Figure 11, for instance, the satisfaction of attribute Structure in 5 implies the satisfaction of attributes Reliability and Redundancy. The analysis for selecting an architecture is based on propagation algorithms presented in [23]. Basically, the idea is to assign a set of initial labels for some attributes of the graph, about their satisfiability and deniability, and see how this assignment leads to the labels propagation for other attributes. In particular, we adopt from [23] both qualitative and a numerical ....
....based on propagation algorithms presented in [23] Basically, the idea is to assign a set of initial labels for some attributes of the graph, about their satisfiability and deniability, and see how this assignment leads to the labels propagation for other attributes. In particular, we adopt from [23] both qualitative and a numerical axiomatization for goal (attributes) modeling primitives and label propagation algorithms that are shown to be sound and complete with respect to their respective axiomatization. In the following, a brief description of the qualitative algorithm. To each ....
P. Giorgini, J. Mylopoulos, E. Nicchiarelli, and R. Sebastiani. Reasoning with goal models. Technical report, Department of Information and Communication Technologies - University of Trento - Italy, 2002.
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