Graduate Course: Distributed Intelligent Multi-Agent Systems
Department of Computer Science
Iowa State University

Distributed Intelligent Multi-Agent Systems
Advanced Topics in Artificial Intelligence and Cognitive Modelling
Spring 2000 Offering

Dr. Vasant Honavar
Associate Professor
Artificial Intelligence Research Laboratory
Department of Computer Science and
Bioinformatics and Computational Biology
210 Atanasoff Hall
Iowa State University
Voice: 515 294-1098, Fax: 515 294-0258

Meeting Time: MW 12:45pm to 2pm
Meeting Place: 217 Atanasoff Hall

Distributed Intelligent Multi-Agent Systems offer modular, flexible, scalable and generalizable algorithms and systems solutions for information retrieval, extraction, fusion, and data-driven knowledge discovery using heterogeneous, distributed data and knowledge sources in information rich, open environments. Such systems consist of multiple interacting intelligent software agents.

Intelligent software agents are software entities that perform a set of tasks on behalf of a user with some degree of autonomy. Such reactive, proactive, anticipatory, goal-driven, adaptive, reflective, introspective, knowledge-seeking, autonomous, interactive, communicative, collaborative agents and multi-agent systems find applications in Internet-based information systems, adaptive (customizable) software systems, large scale data-driven knowledge discovery from heterogeneous, distributed data and knowledge sources, collaborative scientific discovery (e.g., in bioinformatics), intelligent decision support systems (e.g., monitoring and control of complex, distributed, dynamic systems).

Current research on intelligent agents and multi-agent systems builds on developments in several areas of computer science including: artificial intelligence (agent designs, learning, planning, inference, distributed problem-solving), information retrieval, database and knowledge-base systems, and distributed computing.

The Spring 2000 offering of the course will cover selected topics in Distributed Intelligent Multi-Agent Systems with emphasis on the following:

The course will strike a balance between algorithms and techniques that have already been used widely in the field as well as open research problems and approaches at the edge of the state of the art in these fields. The target audience for this course consists primarily of graduate students in Computer Science and Bioinformatics and Computational Biology who are interested in Artificial Intelligence and its applications in bioinformatics, internet-based information systems, self-managing networks, distributed computing, intelligent databases, intelligent sensor networks, etc.

Interested undergraduates or graduate students in other disciplines who have completed ComS 472 with a grade of A- or better are welcome to register for the course.

Prerequisites: An introductory course (senior undergrad or first year grad) course in AI (comparable to ComS 572 (472 DL)) is recommended. However, students with a sufficiently broad background in Computer Science (e.g., a few 500-level CS courses at ISU or comparable courses taken elsewhere) should find the material fairly accessible.

Grading in this course will be based on written assignments (which might include transcribing lecture notes, reading, summarizing, and presenting papers), several individual or group projects involving design, implementation, and applications of software agents and multi-agent systems, and one or two take-home examination(s).

Textbooks and References

There is no required textbook for this course. Recommended texts are:

Additional list of Recommended Reference Books is available here. (Several books on this list are available on reserve at the Iowa State University Library)

Course Materials

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Dr. Vasant Honavar
Director, Artificial Intelligence Research Laboratory
Department of Computer Science
Iowa State University
Atanasoff Hall, Ames, IA 50011-1040 USA
phone: +1-515-294-4377, fax: +1-515-294-0258