By Ana L. C. Bazzan, Sofiane Labidi
This booklet constitutes the refereed court cases of the seventeenth Brazilian Symposium on man made Intelligence, SBIA 2004, held in Sao Luis, Maranhao, Brazil in September/October 2004.The fifty four revised complete papers provided have been conscientiously reviewed and chosen from 208 submissions from 21 nations. The papers are equipped in topical sections on logics, making plans, and theoretical equipment; seek, reasoning, and uncertainty; wisdom illustration and ontologies; typical language processing; computing device studying, wisdom discovery and information mining; evolutionary computing, man made existence, and hybrid structures; robotics and compiler imaginative and prescient; and independent brokers and multi-agent platforms.
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Extra info for Advances in Artificial Intelligence - SBIA 2004: 17th Brazilian Symposium on Artificial Intelligence
Anytime families of tractable propositional reasoners. In International Symposium of Artificial Intelligence and Mathematics AI/MATH-96, pages 42–45, 1996. 5. Mukesh Dalal. Semantics of an anytime family of reasponers. In 12th European Conference on Artificial Intelligence, pages 360–364, 1996. 6. Marcelo Finger and Renata Wassermann. Expressivity and control in limited reasoning. In Frank van Harmelen, editor, 15th European Conference on Artificial Intelligence (ECAI02), pages 272–276, Lyon, France, 2002.
This example is used in . The size of the FD set decrease from 26 to 18. Example 3. This example is depurated in  using Our reduction in RL and Maude obtains the same result without using a closure operator. 5 Conclusions and Future Work In this work we have studied the relation between RL and the treatment of sets of FDs. We have illustrated the difficulties to face the implication problem with a method directly based on FDs logics. We have introduced the notion of atomicminimality, which guides the treatment of sets of FDs in a rewriting style.
Definition 9. Let be a binary relation defined as: if and only if We can now use as the relatedness relation needed to structure the relevance graph, and instantiate the general framework. In the next section, we describe how this approximate inference has been implemented and some results obtained, which show that the use of the relatedness relation does bring some gains in the inference process. TEAM LinG Using Relevance to Speed Up Inference 4 27 Implementation and Results In this section, we show how the framework for approximate inference based on syntactical relevance has been implemented and the results which were obtained.
Advances in Artificial Intelligence - SBIA 2004: 17th Brazilian Symposium on Artificial Intelligence by Ana L. C. Bazzan, Sofiane Labidi