Building Enhanced Markets using AI
How to design assistive AI agents that learn individual user preferences, find top recommended actions out of several options for their user, bid opportunistically on behalf of the user in competing markets, be aware of the changing market conditions, and learn efficiently from past interactions? In this project we study these and other similar compelling questions.
This post is about the general project description. For specific details about the paper “Interactive Learning with Smart Pricing for Optimal and Stable Allocations in Markets” see this post.