Advanced Topics in Artificial Intelligence

Basic information

Workload: 

45 hours

Syllabus: 

Present / deepen basic topics and problem solving techniques in Artificial Intelligence (AI), introducing one or more of the following topics in AI: fuzzy inference systems, neural networks, genetic algorithms, multi-agent systems and distributed AI, complex networks, AI planning and applications, decision support systems, or any other theme that represents the state of the art in AI.

Bibliography

Mandatory: 

  • Bramer, M., & Devedzic, V. (2004). Artificial Intelligence Applications and Innovations. Kluwer Academics.
  • Fulcher, J. (2006). Advances in Applied Artificial Intelligence. Idea Grouping inc.
  • Konar, A. (2000). Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain. CRC Press.
  • Russell, S., & Norvig, P. (2003). Artificial Intelligence: a modern approach. Prentice-Hall Inc.
  • Visser, U. (2005). Intelligent Information Integration for the Semantic Web. Springer.
  • Zhang, Y.-Q., Kandel, A., Lin, T. Y., & Yao, Y. Y. (Eds.). (2004).Computational Web Intelligence: Intelligent Technology for Web Applications. World Scientific Co.