By Phokion G. Kolaitis (auth.), George A. Vouros, Themistoklis Panayiotopoulos (eds.)
Arti?cial intelligence has attracted a renewed curiosity from wonderful sci- tists and has back raised new, extra reasonable this time, expectancies for destiny advances concerning the improvement of theories, versions and strategies and using them in purposes pervading many components of our way of life. The borders of human-level intelligence are nonetheless very distant and doubtless unknown. Nev- theless, contemporary scienti?c paintings evokes us to paintings even more durable in our exploration of the unknown lands of intelligence. This quantity includes papers chosen for presentation on the third Hellenic convention on Arti?cial Intelligence (SETN 2004), the o?cial assembly of the Hellenic Society for Arti?cial Intelligence (EETN). The ?rst assembly used to be held within the collage of Piraeus, 1996 and the second one within the Aristotle college of Thessaloniki (AUTH), 2002. SETN meetings play an enormous position within the dissemination of the in- vative and top of the range scienti?c leads to arti?cial intelligence that are being produced almost always by way of Greek scientists in institutes around the globe. besides the fact that, an important e?ect of SETN meetings is they give you the context during which humans meet and get to grasp one another, in addition to a great opp- tunity for college students to catch up with to the result of cutting edge arti?cial intelligence research.
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Additional resources for Methods and Applications of Artificial Intelligence: Third Hellenic Conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings
This index is used to solve the ﬁltering problem: Given a database of continuous queries db and a notiﬁcation n, ﬁnd all queries q ∈ db that match n and forward n to the neighbouring super-peers or clients that have posted q. 4 Stored Notiﬁcations and Rendezvous at Super-peers Clients may not be online all the time, thus we can not guarantee that a client with a speciﬁc continuous query will be available at the time that matching resources are added to the network and relevant notiﬁcations are generated.
Then, it migrates to all super-peers of the network to search for answers to q. It will start from the super-peer environment of the access point A of C and it will reach all super-peers through the minimum-weight spanning tree of A. Each time, it ﬁnds any resource metadata matching q in a super-peer environment B, it clones itself. The clone returns to the environment of client C to deliver the answer by travelling towards super-peer A through the shortest path that connects B and A. The original query-answering agent will continue in order to visit the rest of the super-peers of the network to search for answers to q.
The conceptual model that we propose can be instantiated in various environments, and this feature is illustrated by a case study concerning the management of distributed eLearning documents. Research supported by the EU DELOS Network of Excellence in Digital Libraries and the EU IST Project (Self eLearning Networks), IST-2001-39045. A. Vouros and T. ): SETN 2004, LNAI 3025, pp. 33–42, 2004. c Springer-Verlag Berlin Heidelberg 2004 34 Birahim Gueye, Philippe Rigaux, and Nicolas Spyratos In Section 2 we discuss the motivations of this work.
Methods and Applications of Artificial Intelligence: Third Hellenic Conference on AI, SETN 2004, Samos, Greece, May 5-8, 2004. Proceedings by Phokion G. Kolaitis (auth.), George A. Vouros, Themistoklis Panayiotopoulos (eds.)