Decision Making in Robots and Autonomous Agents

Semester 2 2013/2014

Level 11 Official course descriptor

Admin:

Course organiser: Iain Murray
For administrative queries, your first point of contact is the ITO. Also see this link.

Lectures:

Lecturer: Subramanian Ramamoorthy
Lecture times: Tuesdays and Fridays 11:10 - 12:00, G.8 Gaddum Lecture Theatre, 1 George Square
Lecture topics and handouts

Assessment:

The course mark will be computed using the following weighting:

Primary Objectives

This course is intended as a specialized course on models and techniques for decision making in autonomous agents, such as intelligent robots, with special emphasis on how they learn to interact with other agents and people. This course will cover four major themes: Note regarding changes to 2013/14 content: Unlike in the previous offering, we will be more focussed on issues of learning, user modelling and adaptation, and less on algorithmic issues arising within game theory or decision theory.

Background and Pre-requisites

This is a 'second course' in the sense that the student taking this course should have had some prior exposure to an application domain requiring the design of autonomous decision making systems. This could be robotics (e.g., through the R:SS course) or a course on agent design in a software setting, e.g., recommender systems.
The student should be proficient in the formulation and use of mathematical models and possess sufficient mathematical maturity in order to be able to follow some readings from the research literature. Specific topical pre-requisites include Calculus & Probability at the level of MATH08063, MATH08067.
On the practical side, one of the assignments will require programming, in an environment such as Matlab. Students are expected to enter this course with sufficient programming skill, or the capacity to learn what is required on the fly. However, this is not a 'programming course' - most of our classroom discussion will focus on algorithmic and conceptual ideas.

Suggested Readings

Last update: 22 January 2014.


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