DATA415-20S2 (C) Semester Two 2020

Computational Social Choice

15 points

Details:
Start Date: Monday, 13 July 2020
End Date: Sunday, 8 November 2020
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Friday, 24 July 2020
  • Without academic penalty (including no fee refund): Friday, 25 September 2020

Description

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.

Pre-requisites

Subject to approval of the Head of Department of Mathematics and Statistics.

Timetable 2020

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Tuesday 16:00 - 18:00 Jack Erskine 242 13 Jul - 23 Aug
7 Sep - 18 Oct
Tutorial A
Activity Day Time Location Weeks
01 Monday 14:00 - 15:00 Rehua 008 Computer Lab 3 Aug - 23 Aug
7 Sep - 18 Oct

Course Coordinator / Lecturer

Gabor Erdelyi

Indicative Fees

Domestic fee $942.00

* Fees include New Zealand GST and do not include any programme level discount or additional course related expenses.

For further information see Mathematics and Statistics.

All DATA415 Occurrences

  • DATA415-20S2 (C) Semester Two 2020