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Portrait of Manxi Wu with header text that states "Colloquium on Digital Transformation Science" and talk title text that states "On Convergence and Stability of Coupled Belief – Strategy Learning Dynamics in Continuous Games." April 14, 2022 @ 1 p.m. PT/3 p.m. CT.

C3.ai DTI Colloquium: On Convergence and Stability of Coupled Belief – Strategy Learning Dynamics in Continuous Games

Event Type
Seminar/Symposium
Sponsor
C3.ai Digital Transformation Institute
Virtual
wifi event
Date
Apr 14, 2022   3:00 pm  
Speaker
Manxi Wu, UC Berkeley Postdoc Researcher
Registration
Required.
Contact
C3.ai Digital Transformation Institute
Originating Calendar
NCSA-related events

C3.ai DTI's Colloquium on Digital Transformation is a series of weekly online talks on how artificial intelligence, machine learning, and big data can lead to scientific breakthroughs with large-scale societal benefits. Open to all – registration required.

Overview
We study a dynamic setting in which a public information platform updates a belief estimate of a continuous game parameter based on available data of strategies and payoffs. Players adjust their strategies by accounting for the repeatedly updated belief. The long-term behavior of the resulting stochastic learning dynamics is based on endogenous and non-i.i.d. data that is generated by players’ strategic decisions. We develop new tools to tackle the dynamic interplay between parameter learning and strategy learning in continuous games. We present results on the convergence and stability of such learning dynamics and develop conditions for convergence to complete information equilibrium. Furthermore, we apply this learning model to analyze the impact of information platforms on the strategic behavior of travelers in urban transportation systems. We show that our results can be used to design adaptive tolling mechanisms with travelers learning their routing decisions in traffic networks.

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