George Mason University
School of Information Technology and Engineering
DEPARTMENT OF COMPUTER SCIENCE

INFT910 - Special Topics in Artificial Intelligence: Intelligent Agents - Fall '96

Thursday 7:20pm-10:00pm, Robinson B205

News | Description| Readings

This page last updated on 8/19/96.


Professor Gheorghe Tecuci
703-993-1722

tecuci@ gmu.edu
(for fastest service prefix the subject of your email with INFT910)

Course office hour Thursday 6:10pm-7:10pm; e-mail all times
ST2 Room 421


NEWS:

To get a computer account at SITE: (1) Obtain an OSF1 account from UCIS. (2) Login to OSF1 and type "sitereg". You will be prompted for your GMU id and will be allowed to create a SITE account on line.

Other relevant class news will be posted here.

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DESCRIPTION :

INFT910 - Special Topics in Artificial Intelligence: Intelligent Agents

Prerequisite: a graduate level course in artificial intelligence or permission of instructor.

An agent is a system situated within and part of an environment that senses that environment and acts on it, over time, in pursuit of its own agenda and so as to effect what it senses in the future (Franklin & Graesser, 96). Intelligent software agents are AI programs that can assist users in various ways. For instance, they can perform tasks on the user's behalf, they can advise, train or teach the user, they can monitor events for the user, or help different users collaborate. This course will review and analyze the basic approaches to building intelligent software agents, as well as representative examples of current agent applications. Particular attention will be given to learning agents that can be directly trained by a user to perform specific tasks, and that can learn from their experience. The course will also discuss open issues, current trends and frontier research in the area of intelligent agents.

The course will consist of a sequence of lectures given by the instructor and student presentations. Students will select papers from a provided list and will present critical reviewes and analyses of representative intelligent agents. Students may also experiment with or enhance the agent building software developed in the Learning Agents Laboratory.

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READINGS:

Recommended readings for each topic and week will appear in this space.
Most of the papers will be available on the Internet.


Overview of intelligent agents



Foundations for building intelligent agents



The Disciple approach to building intelligent agents



Softbots for the Internet



Agents that reduce work and information overload



Learning personal assistants



Agent-based software engineering



Programming agents by example



Teaching agents that learn



Architecture of integrated agents



Enabling agents to work together


Disciple Toolkit Related Projects

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