Undergraduate Course: Agent Based Systems (INFR10072)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Postgraduate) |
| Course type | Online Distance Learning |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | *Not being delivered in 2017-18*
*Only available to students of the Data Science, Technology and Innovation (DSTI) online distance learning programme.*
Agent technology has emerged as a new area within Artificial Intelligence in the last two decades, exploring systems in which it is assumed that the computational components are autonomous, and interact with each other in a common environment. The aim of this course is to provide a comprehensive introduction to agents and multiagent systems. It covers a broad range of topics including agent architectures, agent interaction and communication, and game-theoretic methods and models of distributed rational decision making. This distance-based course is aligned with the on-campus Agent Based Systems course (INFR10049), which uses a flipped classroom delivery approach. |
| Course description |
1. Introduction
2. Formal notation and logic-based modelling
3. Abstract Agent Architectures
4. Deductive Reasoning Agents
5. Practical Reasoning Agents
6. Reactive and Hybrid Agent Architectures
7. Agent Communication
8. Methods for Coordination
9. Multiagent Interactions
10. Social Choice
11. Coalition Formation
12. Resource Allocation
13. Bargaining
14. Argumentation in Multiagent Systems
15. Summary and Concluding Remarks
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | Only available to students of the Data Science, Technology and Innovation (DSTI) online distance learning programme |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
| Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- Describe and evaluate different architectures for intelligent agents and interaction mechanisms for cooperative and competitive settings.
- Use abstract formal models of agents and agent interactions to specify concrete designs and analyse their properties.
- Demonstrate an understanding of the algorithmic and theoretical foundations of agents and multiagent systems, with an emphasis on knowledge-based and game-theoretic techniques.
- Be able to model, analyse and critically evaluate distributed systems using agent-based abstractions and related concepts.
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Reading List
- M. Wooldridge. An Introduction to MultiAgent Systems, 2nd edition, John Wiley & Sons, 2009
- Y. Shoham and K. Leyton-Brown. Multiagent Systems: Algorithmic, Game Theoretic and Logical Foundations, Cambridge University Press, 2009. |
Additional Information
| Graduate Attributes and Skills |
Problem solving, Analytical thinking, Handling complexity and ambiguity, Independent learning and development. |
| Additional Class Delivery Information |
Flipped classroom. |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Michael Rovatsos
Tel: (0131 6)51 3263
Email: mrovatso@inf.ed.ac.uk |
Course secretary | Mrs Victoria Swann
Tel: (0131 6)51 7607
Email: Vicky.Swann@ed.ac.uk |
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