Artificial Intelligence Research Seminar Computational Inference, Learning, and Discovery Artificial Intelligence Research Laboratory Department of Computer Science Iowa State University

Artificial Intelligence Research Seminar Com S 610 (VH) Spring 2002 will meet once a week. AI seminar will be coordinated by Jun Zhang and Vasant Honavar. The seminar will focus on computational models, algorithms, and software systems for automated or computer-assisted scientific discovery. Topics to be discussed include:

• Computational models of scientific discovery
• Inference of causal relations
• Ontology-assisted data integration and information extraction
• Ontology-driven learning
• Learning ontologies from data
• Distributed learning and multi-agent learning
• Multi-label learning
• Selected applications in computational molecular biology and information security.

Participation

Interested students can sign up for 1-3 credits. One or more seminar participants will be assigned to lead the discussion every week. These discussion leaders will not only present the papers assigned for that week, but also present the relevant background material from other related literature. Discussion leaders are responsible for distributing the readings to seminar participants. One copy of the readings will be available for checkout in the AI lab. All participants will be expected to read the papers in advance and actively contribute to the discussions.

Seminar Schedule

• January 16. Brief research updates from everyone in the lab.
• January 23. INDUS Project: Overview and Current Status, Vasant Honavar
• Readings:
  1. Honavar V., Andorf, C., Caragea, D., Silvescu, A., Reinoso-Castillo, J., and Dobbs, D. (2001). Ontology-Driven Information Extraction and Knowledge Acquisition from Heterogeneous, Distributed, Autonomous Biological Data Sources In: IJCAI Workshop on Knowledge Discovery from Heterogeneous, Distributed, Dynamic, Autonomous Data and Knowledge Sources. International Joint Conference on Artificial Intelligence (IJCAI 2001) Seattle, Washington, August 2001.
  2. Caragea, D., Silvescu, A., and Honavar, V. (2001). Invited Chapter. Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources. I n: Emerging Neural Architectures Based on Neuroscience. Berlin: Spring er-Verlag.
  3. Caragea, D., Silvescu, A., and Honavar, V. (2002). Invited Chapter. Multi-agent Decision Tree Learning from Distributed Data Sources. In: Intelligent Agent Software Engineering. Plekhanova, V. and Wermter, S. (ed.). Idea Group Publisher. To appear.