By Jaime Simao Sichman, Helder Coelho, Solange Oliveira Rezende
This booklet constitutes the refereed court cases of the 2d foreign Joint convention of the tenth Ibero-American convention on synthetic Intelligence, IBERAMIA 2006, and the 18th Brazilian synthetic Intelligence Symposium, SBIA 2006, held in Riberão Preto, Brazil in October 2006.
The sixty two revised complete papers offered including four invited lectures have been rigorously reviewed and chosen from 281 submissions. The papers are equipped in topical sections on AI in schooling and clever tutoring platforms, self sustaining brokers and multiagent structures, desktop imaginative and prescient and development attractiveness, evolutionary computation and synthetic lifestyles, hybrid structures (fuzzy, genetic, neural, symbolic), wisdom acquisition and laptop studying, wisdom discovery and knowledge mining, wisdom engineering, ontologies and case dependent reasoning, wisdom illustration and reasoning, common language processing, making plans and scheduling, robotics, theoretical and logical equipment, in addition to uncertainty.
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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
The present study addresses the research question: Are PAS or GAS feedback strategies more eﬀective for teaching the Spanish subjunctive mood for foreign language learners? by addressing the following hypotheses: – Hypothesis 1: Learners who receive PAS after their subjunctive errors will show greater ability to produce this mood correctly, as measured by pre-test post-test gain scores, than learners not exposed to this feedback. – Hypothesis 2: Learners who receive GAS after their subjunctive errors will show greater ability to produce this mood correctly, as measured by pre-test post-test gain scores, than learners not exposed to this feedback.
Using a MAS approach in designing ITS and ILE can result in faster, more versatile and low cost systems. Agents composing such systems are called Pedagogical Agents. Our research group has been working with these kinds of systems for e-learning , , . Despite all technological advances that the agents add to our learning systems, our agents are not reusable in various courses and in different situations because they cannot interoperate with other learning environments or agents outside their societies.
Thus, the framework provides services to perform server tasks and client tasks for all the dialogues as shown above. The task classes are ready to be used by the agents. A. R. Gomes, and R. Viccari the three types of agents defined in the agent society. These classes perform the main tasks defined for the society’s agent, like answering for metadata requests. Figure 3 shows this software architecture. The agent classes extend the FIPAOSAgent class from the FIPA-OS framework. The tasks classes extend the Task class from the FIPA-OS.
Advances in Artificial Intelligence - IBERAMIA-SBIA 2006: 2nd International Joint Conference, 10th Ibero-American Conference on AI, 18th Brazilian AI by Jaime Simao Sichman, Helder Coelho, Solange Oliveira Rezende