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 ICS 486: Multi-Agent Systems

​Course Information

Class/Laboratory Schedule: 

Three 50 minutes lectures per week (3-0-3)

Designation:   Elective Course

Course Level:   Undergraduate


Prerequisite(s) by Topic: 

  • A familiarity with Programming Fundamentals.
  • Communication and networking
  • Building Web applications

Prerequisite Courses: 

Catalog Description: 

Agents, agent definitions and classification; Multi-agent systems (MAS) and their characteristics; Models of agency, architectures and languages, logics for MAS, deductive and practical reasoning agent, reactive and hybrid agents; Distributed problem solving and planning; Coordination mechanisms and strategies; Learning in MAS; Interaction, negotiation and coalition formation; Applications of agent technology (agents in electronic commerce and information retrieval.


M. Wooldridge, An Introduction to Multi-Agent Systems, John Wiley and Sons Ltd, February 2002.

Reference(s) and Other Material: 

  • Lin Padgham, Michael Winikoff, Developing Intelligent Agent Systems: A Practical Guide, John Wiley & Sons (2004).
  • Gerhard Weiss, Multi-agent systems: A modern approach to distributed artificial intelligence, the MIT press, 1999, Amazon.

Course Outcomes: 

After completion of this course, the student shall be able to:

  • Identify and analyze what are agents, MAS and what are their characteristics.
  • Distinct agents from other software paradigms (e.g. objects, expert systems).
  • Understand the main application areas of agent-based solutions.
  • Understand what are mobile agents? & what are their characteristics?
  • Use the methods and tools of the AI (learning, adaptation, planning, searching, and reasoning) for designing and evaluating the agent systems.
  • Understand how to construct agents capable of acting autonomously using contemporary (Java-based) framework for programming agents (e.g., JACK, JADE, CYBELE PRO, RETSINA) tools.

Topics Covered: 

  • Intelligent agent’s definitions and classification, Multi-Agent Systems (MAS).
  • Models of agency and architectures.
  • Logics for MAS.
  • Learning in MAS.
  • Deductive and practical reasoning agent.
  • Reactive and hybrid agents.
  • Agent communication languages and interaction protocols (KQML, FIPA-ACL, KIF) framework).
  • Reaching agreements.
  • Cooperative distributed problem solving and planning.
  • Negotiation and coalition formation.
  • Mobile agents.
  • Formal methods in agent-oriented software engineering.
  • Agent programming tools: JADE, IMPACT, RETSENA, JACK, CYBELEPRO.
  • Agents-based application for Intelligent Tutoring System, for distributed network sensing, for traffic control system, E-Commerce, Internet browsing guide.​