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Course Description and Outline

The course begins with an overview of the agent systems and software agents. Then we focus on multi-agent systems, from an AI perspective, including:

  • Agent Communications and Ontologies
  • Distributed Search in AI
  • Distributed Rational Decision Making
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.   

Course Objectives

Agent, 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:
  • 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 Communication?
After taking this course, the participants
  • will have an understanding of the agent itself, its suggested architectures, and its applications
  • will have an understanding of multi-agent systems.
  • will know how agents communicate, share knowledge, learn as a group, cooperate, negotiate, etc.

Course syllabus

The course syllabus can be found in the syllabus page and also in PowerPoint format.

Course book

  • Multiagent Systems A Modern Approach to Distributed Artificial Intelligence by Gerhard Weiss 1999
  • An 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 page.

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 Criteria

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 assignments.

Criteria Total mark Comments
Exams 40% 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.

Project 40% 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 agent.
Homework 20% These are assigned on a weekly basis. The deadline for each assignment is the Tuesday of next week.
 

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