skip to main content

Rigorous Systems Research Group Seminar

Monday, March 4, 2019
12:00pm to 1:00pm
Add to Cal
Annenberg 213
One if by Land and Two if by Sea: A Glimpse into the Value of Information in Strategic Interactions
Vijay Subramanian, Associate Professor, Electrical Engineering and Computer Science, University of Michigan,

This work studies sequential social learning (also known as Bayesian observational learning), and how private communication can enable agents to avoid herding to the wrong action/state. Starting from the seminal BHW (Bikhchandani, Hirshleifer, and Welch, 1992) model where asymptotic learning does not occur, we allow agents to ask private and finite questions to a bounded subset of their predecessors. While retaining the publicly observed history of the agents and their Bayes rationality from the BHW model, we further assume that both the ability to ask questions and the questions themselves are common knowledge. Then interpreting asking questions as partitioning information sets, we study whether asymptotic learning can be achieved with finite capacity questions. Restricting our attention to the network where every agent is only allowed to query her immediate predecessor, an explicit construction shows that a 1-bit question from each agent is enough to enable asymptotic learning.

This is joint work with Shih-Tang Su and Grant Schoenebeck at the University of Michigan. Details of the work can be found at .

For more information, please contact Yu Su by email at [email protected].