Academics / Courses / DescriptionsCOMP_SCI 396: Algorithms for Collective Decision Making
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Prerequisites
CS 335 or 336 or CS MS or CS PhD or Instructor permissionDescription
The purpose of this course is to explore collective decision making from an algorithmic point of view. We study settings where groups of agents need to make a joint decision by aggregating preferences of individual group members. Examples include (1) coalition formation, where agents need to split into teams and have preferences over teams they can be part of, (2) voting, i.e., selecting one or more candidates to represent the group, or one or more projects to be implemented, (3) fair allocation, i.e, distributing a set of items (or a single divisible item) among the agents in a fair and efficient way. We will consider both normative properties (such as axioms and fairness requirements) and algorithmic aspects of the proposed solutions (polynomial-time algorithms and NP-hardness results) Syllabus.
- This course fulfills the Technical Elective area.
REQUIRED TEXTBOOK: N/A
COURSE COORDINATORS: Prof. Elkind
COURSE INSTRUCTOR: Prof. Elkind (Spring)