ECE408

Agent-Based Simulation
Fall 2012
Designation: 
Technical Elective for ECE
Catalog Data: 

ECE 408 -- Agent-Based Simulation  (3 units)
Description:  This course will introduce the student to: the concept of agents and multi-agent systems; the main issues in the theory and practice of multi-agent systems; the design of multi-agent systems; contemporary platforms for implementing agents and multi-agent systems; artificial life, artificial societies, N-person games. Upon completing this course, the students will understand: the notion of an agent; how agents are different from other software paradigms; the key issues associated with constructing agents, building and implementing models; the main approaches to developing agent-based simulation systems; the types of multi-agent interactions possible in such systems; the main application areas of agent-based simulation. Most importantly, they will be able to develop meaningful agent-based systems.
Grading:  Regular grades are awarded for this course: A B C D E.
May be convened with:  ECE 508.
Usually offered:  Spring

 
Prerequisite(s): 
ECE 175 or a strong foundation in a programming language.
Textbook(s): 

Agent-Based and Individual-Based Modeling: A Practical Introduction by Steven F. Railsback & Volker Grimm. Princeton University Press, 2011

Course Learning Outcomes: 

By the end of this course, the student will understand:

  1. The notion of an agent
  2. NetLogo and other contemporary platforms for implementing agent-based simulation
  3. The key issues associated with constructing agents, building and implementing models
  4. The main approaches to developing agent-based simulation systems
  5. The types of multi-agent interactions possible in such systems
  6. The main application areas of agent-based simulation
  7. Most importantly, they will be able to develop meaningful agent-based systems
Course Topics: 
  • Agents, objects, distributed systems.
  • Multi-agent nonlinear stochastic systems.
  • Agent personalities.
  • Intelligent agents.
  • Mobile agents.
  • History of multi-agent systems research.
  • Distributed Artificial Intelligence.
  • Complex systems.
  • Cellular automata.
  • N-person games.
  • Cooperation, coalitions, auctions, negotiations, bargaining.
  • Artificial life.
  • Agent simulation as a tool for understanding human societies. Social networks and dilemmas.
  • Agent simulation in Game Theory, Economics, Biology, Sociology, Political Science, etc.
  • Design and implementation of multi-agent models.
  • Computational techniques for agent-based simulation.
  • Agent simulation design methodologies.
  • NetLogo and other pPlatforms for implementing agent-based simulation.
  • Pitfalls of agent development. 
  • Applications of agent systems to real-life problems.
  • Case studies.
Class/Laboratory Schedule: 

Two 75-minute lecture sessions per week.

Relationship to Student Outcomes: 

a) an ability to apply knowledge of mathematics, science, and engineering (Medium)
c) an ability to design a system, component, or process to meet desired needs within realistic
    constraints such as economic, environmental, social, political, ethical, health and safety,
    manufacturability, and sustainability (Medium)
e) an ability to identify, formulate, and solve engineering problems (High)
g) an ability to communicate effectively (Medium)
h) the broad education necessary to understand the impact of engineering solutions in a global,
    economic, environmental, and societal context (Medium)
k) an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. (High)

Prepared Date: 
Dr. Miklos Szilagyi
Modifications By: 
2/1/10

University of Arizona College of Engineering