By Frank Dignum (auth.), Jaime Simão Sichman, Helder Coelho, Solange Oliveira Rezende (eds.)
The Brazilian Arti?cial Intelligence (AI) group made up our minds in 2004 to arrange a global Joint convention, becoming a member of IBERAMIA 2006 (the tenth Ibero-American Arti?cial Intelligence Conference), SBIA 2006 (the 18th Brazilian Arti?cial Int- ligence Symposium), and SBRN 2006 (the ninth Brazilian Neural Networks Sym- sium). This determination was once a outcome of the winning occasion equipped in 2000, whilst the 1st foreign Joint convention IBERAMIA/ SBIA 2000 (7th Ibero- American Arti?cial Intelligence convention and fifteenth Brazilian Arti?cial Intel- gence Symposium) happened in Brazil. furthermore, in 2006 the arti?cial intelligence neighborhood celebrated the golden anniversary of the 1956 Dartmouth convention that marked the start of arti?cial intelligence as a study ?eld. th SBIA 2006 used to be the 18 convention of the SBIA convention sequence, that is the top Brazilian convention for the presentation of AI examine and purposes. when you consider that 1995, SBIA has turn into a world convention, with papers written in English, a global application Committee, and court cases released in Springer’s Lecture Notes in Arti?cial Intelligence (LNAI) sequence. th IBERAMIA 2006 was once the ten convention of the IBERAMIA convention - ries, which has been essentially the most appropriate boards for Ibero-American AI researchers (from South and principal American international locations, Mexico, Spain and Portugal) to provide their effects. Following the SBIA and EPIA (Portuguese convention on AI) studies, from IBERAMIA 1998 on, it has additionally develop into a global convention with complaints released in Springer’s LNAI series.
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Extra resources for Advances in Artificial Intelligence - IBERAMIA-SBIA 2006: 2nd International Joint Conference, 10th Ibero-American Conference on AI, 18th Brazilian AI Symposium, Ribeirão Preto, Brazil, October 23-27, 2006. Proceedings
E Comp. pt Abstract. g. an earthquake or a terrorist incident, urges for low-cost policies that coordinate sequential decisions of multiple agents. Decisions range from collective (common good) to individual (self-interested) perspectives, intuitively shaping a two-layer decision model. However, current decision theoretic models are either purely collective or purely individual and seek optimal policies. We present a two-layer, collective versus individual (CvI) decision model and explore the tradeoff between cost reduction and loss of optimality while learning coordination skills.
Michelene T. H. Chi, Stefanie Siler, H. Jeong, T. Yamauchi, and Robert G. Hausmann. Learning from tutoring. Cognitive Science, 25(3):471–533, 2001. 3. C. Graesser, S. T. Jackson, H. Mitchell, M. Ventura, A. M. Louwerse. Autotutor: A tutor with dialogue in natural language. Behavioral Research Methods, Instruments, and Computers, 36:180–193, 2004. 4. G. Hume, J. Michael, A. Rovick, and M. Evens. Hinting as tactic in one-on-one tutoring. Journal of Learning Sciences, 5(1):23–47, 1996. 5. L. Levin and D.
The following section reveals some of the basic concepts. Then there is a presentation of the ILO Multi-Agent architecture with its communication structure and a case study showing the use of ILO concepts to improve interoperability among pedagogical agents and learning objects. 2 Intelligent Learning Objects For this research, an Intelligent Learning Objects (ILO) is an agent enabled to promote learning experiences to students the same way as learning objects do. For this reason, an ILO can be also seen as a learning object built through the agent paradigm.