By Jaime Simao Sichman, Helder Coelho, Solange Oliveira Rezende
This booklet constitutes the refereed lawsuits of the second foreign Joint convention of the tenth Ibero-American convention on man made Intelligence, IBERAMIA 2006, and the 18th Brazilian man made Intelligence Symposium, SBIA 2006. The e-book offers sixty two revised complete papers including four invited lectures. Topical sections comprise AI in schooling and clever tutoring structures, self sufficient brokers and multiagent structures, machine imaginative and prescient and development acceptance, evolutionary computation and synthetic existence, and more.
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Additional resources for Advances in Artificial Intelligence - IBERAMIA-SBIA 2006: 2nd International Joint Conference, 10th Ibero-American Conference on AI, 18th Brazilian AI ... 2006 (Lecture Notes in Computer Science)
Figure 6 shows this communication structure. Fig. 5. Communication structure Intelligent Learning Objects: An Agent Approach 25 5 Conclusions Intelligent Learning Objects are able to improve the adaptability, interoperability and interactivity of learning environments built with these kinds of components by the interaction among the learning objects and between learning objects and other agents in a more robust conception of communication rather than a single method invocation as the object-oriented paradigm use to be.
The result is that communication by ACL and CL is potentially much better than the communication done by the object oriented approach as the current learning object models do. Another interesting useful capability of intelligent agents concerns their potential learning ability. This feature gives ILOs the ability to acquire new knowledge and perform different behaviors during its existence, as according to its own experience. Thus, by interaction with students and other ILOs, an ILO is able to evolve.
1 Standard for Learning Object Metadata and to add the server class of the get-metadata dialogue. With this simple change we enabled the discoverability in this pedagogical agent. We then added the client task of the dialogue put-learner-lms and the server task of the dialogue put-learner-ilo. 1 Standard for Learning Technology – Data Model for Content Object Communication in order to communicate with other pedagogical agents. This agent was also implemented using the FIPA-OS. Thus, we just added the mentioned tasks in its main class and changed its behavior a little to get the tasks instantiated when necessary.