DATA415-21S2 (C) Semester Two 2021

Computational Social Choice

15 points

Details:
Start Date: Monday, 19 July 2021
End Date: Sunday, 14 November 2021
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 1 August 2021
  • Without academic penalty (including no fee refund): Friday, 1 October 2021

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.

Learning Outcomes

1. An overall understanding of computational social choice, especially decision making in the presence of big datasets.
2. An understanding of strategic behaviour in preference aggregation.
3. A basic knowledge of proof concepts in computational complexity.
4. The capability of designing algorithms and mechanisms for decision-making purposes in the presence of big data sets.  
5. Acquired the capacity to work independently and manage their time in order to meet course deadlines.

Pre-requisites

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

Timetable 2021

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Wednesday 13:00 - 15:00 Jack Erskine 505
19 Jul - 29 Aug
13 Sep - 24 Oct
Tutorial A
Activity Day Time Location Weeks
01 Wednesday 12:00 - 13:00 Jack Erskine 442 Computer Lab
9 Aug - 29 Aug
13 Sep - 24 Oct

Course Coordinator / Lecturer

Gabor Erdelyi

Indicative Fees

Domestic fee $952.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

All DATA415 Occurrences

  • DATA415-21S2 (C) Semester Two 2021
  • DATA415-21S2 (D) Semester Two 2021 (Distance)