By José Júlio Alferes, Luýs Moniz Pereira, Halina Przymusinska, Teodor C. Przymusinski (auth.)
This e-book constitutes the refereed lawsuits of the ninth foreign convention on man made Intelligence: method, structures, and purposes, AIMSA 2000, held in Varna, Bulgaria in September 2000.
The 34 revised complete papers offered have been rigorously reviewed and chosen from 60 submissions. The papers are prepared in topical sections on wisdom development, reasoning below simple task, reasoning lower than uncertainty, actors and brokers, net mining, traditional language processing, complexity and optimization, fuzzy and neural structures, and algorithmic learning.
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This ebook constitutes the refereed lawsuits of the ninth foreign convention on man made Intelligence: method, structures, and functions, AIMSA 2000, held in Varna, Bulgaria in September 2000. The 34 revised complete papers provided have been conscientiously reviewed and chosen from 60 submissions. The papers are equipped in topical sections on wisdom development, reasoning less than simple task, reasoning below uncertainty, actors and brokers, net mining, typical language processing, complexity and optimization, fuzzy and neural structures, and algorithmic studying.
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Extra info for Artificial Intelligence: Methodology, Systems, and Applications: 9th International Conference, AIMSA 2000 Varna, Bulgaria, September 20–23, 2000 Proceedings
Architecture of TRACS for testing regulations [den Haan, 1996] generator”. which produces all possible situations; legal or illegal. There is no user to feed the system – it runs in batch mode – and only the outputs are checked. The legal reasoning starts when a situation description is fed into the Regulation Applier. This component is a simple production system that matches the situation description to the representation of the regulation in the Legal Source. A legal norms is represented as a generic situation description with functions that represent the deontic operators and yield “allowed/disallowed” as output when applied to a situation description.
It often happens that these computation problems are NP-hard, and it is necessary to work out heuristics or genetic algorithms. 5 Conclusion From the results of postulates’ analysis it is possible to determine a consensus for given conflict situation if the structure of versions are known. Future works should be concentrated on investigation when a consensus is good enough for given conflict. In other words, from Theorem 2 we can always determine consensus, but the question is if this consensus is sensible or given conflict situation is susceptibility to consensus?
Also in Proceedings of the 11th Belgium-Netherlands Conference on Artiﬁcial Intelligence (Maastricht, November 3-4, 1999). , and Bosscher, D. Intelligent information serving for the legal practitioner. In Proceedings of the IASTED Conference on Law and Technology, LawTech-99 (1999), pp. 103–114. , and den Haan, N. Automated legislative drafting: Generating paraphrases of legislation. , ACM, pp. 112–118. 27 Steps towards C+C: A Language for Interactions Stefano A. fr Abstract. We present in this paper our reflections about the requirements of new architectures and languages for the Web, confronted with the ones emerging from qualified scientists such as Mc Carthy  and Wegner .