Data and Information Markets Seminar Series

Algorithmic Persuasion through Simulation

March 29, -
Speaker(s): Nicole Immorlica


In the standard persuasion setup, a sender uses knowledge about a receiver's beliefs to persuade her to take certain actions. However, in many settings the sender may only have limited information about the receiver she is trying to persuade. Motivated by recent empirical research showing that Generative AI can simulate economic agents, we introduce a model of persuasion in which the sender is uncertain about the receiver's beliefs, but has access to an oracle which can simulate the receiver's behavior under any messaging policy. These simulations allow the sender to refine her information about the receiver, enabling her to be more persuasive. We show how the sender can leverage her ability to simulate the receiver in order to design querying policies which maximize her utility. Algorithmic Persuasion Through Simulation is joint work with Keegan Harris, Brendan Lucier and Alex Slivkins.

Speaker Bio

Nicole Immorlica is a senior principal researcher at Microsoft Research New England (MSR NE) where she leads the economics and computation group.  She received her BS in 2000, MEng in 2001 and PhD in 2005 in theoretical computer science from MIT in Cambridge, MA.  She joined MSR NE in 2012 after completing postdocs at Microsoft in Redmond, WA and Centruum vor Wiskunde en Informatics (CWI) in Amsterdam, Netherlands, and a professorship in computer science at Northwestern University.  Nicole‚Äôs research interest is in the design and operation of sociotechnical systems. Using tools and modeling concepts from both theoretical computer science and economics, Nicole hopes to explain, predict, and shape behavioral patterns in various online and offline systems, markets, and games. She is known for her work on social networks, matching markets, and mechanism design.  She is the recipient of a number of fellowships and awards including ACM Fellow, the Sloan Fellowship, the Microsoft Faculty Fellowship and the NSF CAREER Award.  She has been on several boards including SIGecom, SIGACT, the Game Theory Society, and OneChronos; is an associate editor of Operations Research and Transactions on Economics and Computation, and was program committee member and chair for several ACM, IEEE and INFORMS conferences in her area.

About Data and Information Markets

Data and Information Markets is a new seminar series run collaboratively by the Computer Science department and the Decision Sciences area of the Fuqua Business School at Duke University. Our goal is to build a community at Duke around the theme of the economics of data and information, connecting researchers in algorithms, data management, economics, machine learning, medicine, and decision sciences.


Kamesh Munagala