Use the Tab and Up, Down arrow keys to select menu items.
For further information see Mathematics and Statistics
This course provides a thorough introduction to both classical and computational social choice. Social choice theory is the study of mechanisms for collective decision making, such as voting rules or protocols for fair division. Computational social choice addresses problems at the interface of social choice theory with computer science, it uses concepts from social choice theory in the presence of big datasets. This course will introduce some of the fundamental concepts in social choice theory and how they are used in today's data science. The topics covered include material in voting theory, preference aggregation, judgment aggregation, and fair division.
Subject to approval of the Head of Department of Mathematics and Statistics.