CompSci 767:  Intelligent Software Agents

 

COMPSCI 767: Intelligent Software Agents Semester 1 2018

 

1 Course description

This course will look at intelligent software agents in multi-agent settings and as an individual intelligent software agent. 

A multi-agent system consists of multiple interacting agents who share the same environment. Such systems are useful for multi-party, complex, real-time problems with uncertainty that are often impossible or hard to model or solve using a single agent alone. Applications of multi-agent systems range from negotiation, cooperating robots,  market and auction analysis, to security. A main theme in this field involves strategic agents where game theory is an important tool. We will be looking at the algorithmic and game-theoretic foundations of multi-agent systems in this course.

One of the core abilities of an intelligent agent is to be able to solve problems. Search is a general purpose technique for finding solutions to problems. However, these search spaces can be quite large and we need to be able to reduce the size of the search space in order to solve problems in a reasonable amount of time and space. We will be exploring several state of the art techniques for reducing the size of these search spaces.

2 Learning outcomes

The students will be able to:

• Multi-agent systems
  • to understand what a multi-agent system (MAS) is and when they are useful
  • to be able to explain important challenges of MAS such as coordination and cooperation
  • to be able to apply some well-known distributed optimization algorithms
  • to phrase MAS scenarios using the language of game theory
  • to be able to identify or derive equilibria in normal form or extensive form games
• Intelligent software agent
  • to understand current research papers in Heuristic Search
  • to present problems in PDDL, the standard language for describing planning problems
  • to understand some of the tradeoffs involved in using current
    techniques to reduce the problem space sizes
  • to create domain-specific heuristics 
  • to understand some of the tradeoffs involved in creating heuristics

3 Teaching staff

Mike Barley (Coordinator)

Room: 488, Computer Science Building (Building 303S)

Phone: 373-7599, Ext 86133

Email: barley@cs.auckland.ac.nz

 

Jiamou Liu

Room 487, Computer Science Building (Building 303S)

Phone 373-7599, Ext 89528

 Email: Jiamou.liu@cs.auckland.ac.nz

 

4 Lecture Times

Mon 3pm Room 104-155 (Old Choral Hall Room 155)

Tues 4pm Room 303-B11 (Sci/Maths/Physics Room B11)

Fri 3pm Room302-G20  (Science Room G20)

 

5 Assessments

Your final grade will consist of a number of internal marks worth 50% combined and an exam worth 50%. There will be two assignments worth 15% each and two reading assignments worth 10% each.

 

5.1 Internal Marks

Assignment 1 iwill be available on XXX and due via the dropbox on 22 April by 11:59pm

Assignment 2 will be available on 23 April and due via the dropbox on 25 May

 

6 Proposed lecture schedules (subject to change)

Week 1Introduction to Multi-agent System

Week 2 Distributed Optimization Problem

Week 3 Economical and Social Paradigms of Multi-agent System

Week 4 Introduction to Game

Week 5 Finding Equilibriua in Game

Week 6 Reinforcement Learning

Week 7 Review of Search Techniques

Week 8-12 Research Paper Reading and Presentations

StudentPaperSignUp.org

7 Seeking assistance

The primary source of assistance is the teaching staff. Please contact Mike or Jiamou with any questions or concerns about the course. Both are available via email.

 

For help with more generic study skills or literacy, the Student Learning Centre and Library both offer many courses designed to help students become more efficient at study.

 

7.1 Missed lectures

Overhead slides and recommended reading will be provided. Please review the material prior to seeing the teaching staff. If you know in advance that you will miss a lecture, please let the course coordinator know.

 

7.2 Exam

The final exam is worth 50% of your final mark. Please check Student Services Online for the exam time and date. The exam is closed book, calculators are not permitted. Provisional exam results can be obtained from Student Services Online.

 

7.3 Missed exam

If you miss the exam for any valid reason, or you sit the exam but believe that your performance was impaired for some reason, then you may be able to apply for an aegrotat, compassionate or special pass consideration. For more detailed information, refer to pages 44–45 of the University of Auckland’s 2012 Calendar.

 

7.4 Policy on Cheating and Plagiarism

Cheating is viewed as a serious offence by the University of Auckland. Penalties are administered by the Discipline Committee of the Senate, and may include suspension or expulsion from the university. Do not copy anyone else’s work, or allow anyone else to copy from you.

 

For more information on the University’s policy on cheating, please refer to the web page: http: //www.auckland.ac.nz/uoa/home/about/teaching-learning/honesty

 

Exam Info On Mike's Part topics