- Ementa:
- This course advances the study of intelligent systems in knowledge-based engineering by focusing on advanced modeling, reasoning, and decision-making techniques in complex and uncertain environments. It emphasizes hybrid intelligent systems integrating Artificial Intelligence, machine learning, and Paraconsistent Annotated Evidential Logic Eτ. Topics include knowledge representation, neuro-symbolic integration, explainable AI, and scalable decision architectures. The course explores cutting-edge applications in Industry 4.0, cyber-physical systems, logistics, and smart manufacturing, with strong emphasis on research development, critical evaluation of scientific contributions, and the design of innovative intelligent solutions.
- Bibliografia:
- ABE, Jair Minoro. Paraconsistent Intelligent-Based Systems: New Trends in the Applications of Paraconsistency. Cham: Springer, 2015.
- ROBINSON, John Alan; VORONKOV, Andrei (ed.). Handbook of Automated Reasoning. Amsterdam: Elsevier; MIT Press, 2001.
- RUSSELL, Stuart; NORVIG, Peter. Artificial Intelligence: A Modern Approach. 4. ed. Hoboken: Pearson, 2020.
- Bibliografia Complementar
- ZADEH, Lotfi A. Fuzzy sets. Information and Control, v. 8, n. 3, p. 338-353, 1965.
- Explainable Artificial Intelligence – Recent survey papers.
- Neuro-symbolic AI – Recent journal and conference publications.