COMP4640 Reinforcement Learning and Planning Under Uncertainty
Later Year Course
| Offered By | Department of Computer Science |
|---|---|
| Academic Career | Undergraduate |
| Course Subject | Computer Science |
| Offered in | COMP4640 will not be offered in 2009 |
| Unit Value | 6 units |
| Course Description | This course provides an introduction to reinforcement learning (RL) and planning under uncertainty, thereby providing concepts for understanding and developing intelligent systems. For instance, the world-class Backgammon program, TD-Gammon, is based on RL techniques. Topics covered will be the classical MDP model, temporal difference learning, dynamic programming, structured models, approximation algorithms, integrating planning and learning, and the theory of universal rational agents based on sequential decision theory and algorithmic information theory. |
| Indicative Assessment | Two written assignments (15% each); Written Examination (70%) |
| Workload | Thirteen three hour lectures |
| Areas of Interest | Computer Science |
| Recommended Courses |
COMP3620 Artificial Intelligence and /or COMP4670 Introduction to Statistical Machine Learning |
| Consent Required | Consent is required prior to enrolling in this course. |
The information published on the Study at ANU 2009 website applies to the 2009 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2008 website.
