Course Description and Outline
course begins with an overview of the agent systems and software
agents. Then we focus on multi-agent systems, from an AI perspective, including:
Topics such as agent
architecture, communication, knowledge sharing, knowledge representation,
and rational decision making are discussed. A detailed discussion of
distributed search, as well as real-world applications of agents and
multi-agent systems follows.
- Agent Communications and Ontologies
- Distributed Search in AI
- Distributed Rational Decision Making
Course ObjectivesAgent, a relatively new term in computer science
in general and AI in particular, has drawn much attention because of the its
seemingly high potential for tasks usually thought of as possible only by
humans. Several important topics and questions are:
After taking this course, the participants
- What is an agent (i.e. difference between agents and objects, etc.) ?
- What are the benefits (and probably troubles) of using Agents rather
than Non-Agents (Objects for example) ?
- What Architectures exist for design and implementation of agents?
- What are the concepts, advantages and challenges of Agent
- will have an understanding of the agent itself, its suggested
architectures, and its applications
- will have an understanding of
- will know how agents communicate, share
knowledge, learn as a group, cooperate, negotiate, etc.
The course syllabus can be found in the
syllabus page and also in
- Multiagent Systems
A Modern Approach to Distributed Artificial
Gerhard Weiss 1999
Introduction to MultiAgent Systems
by Michael Wooldridge, John Wiley & Sons, 2002
for further reading:
- Multi-Agent Systems. by J Ferber, Addison-Wesley, 1999.
- Foundations of Distributed AI, by G M P O'Hare and N R
Jennings, editors, Wiley Interscience, 1996.
- Readings in Agents, by M Singh and M Huhns,
Morgan-Kaufmann Publishers, 1997.
A more complete list of books can be found at
Course Web Site
The course home page contains links to up-to-date course information, problem
assignments announcements, as well as laboratory and examination scheduling. The
course home page is available at the URL:
DAI course home page
Evaluation is based on tests, project, and assignments. There will be extra
bonus for paper-quality reports prepared based on the project or on any of the
||There is a Midterm and Final Exam, that together determine 40% of the
score each student achieves.
The Midterm exam is closed book, while the final exam is open book.
|| Each group is supposed to hand in the following items:
- An Agent Designed and Implemented to participate in the
TAC-SCM Competition. This includes
both the source code and an executable form.
- The set of Documents corresponding to design and implementation of the
||These are assigned on a weekly basis. The deadline for each assignment is
the Tuesday of next week.