My research is driven by the goal to design
autonomous systems that can improve our quality of life by, for
instance, making it easier to collect information, make decisions, or
predictions. I design and utilize methods at the interface between computer science and economics, specifically around
the intersections among multi-agent, multi-robot and sensor systems, game theory and computational economics.
Distributed Prediction Markets based on Weighted Bayesian Graphical Games
We develop a framework to model a novel, yet practical setting of prediction markets called distributed prediction markets, where the aggregated price of a security of an event in one prediction market is affected dynamically by
the prices of securities of similar events in other, simultaneously running prediction markets.
We propose an ad-hoc collaboration framework where each agent strategically
selects capabilities to learn from other agents which would help
it to improve its expected future utility of performing tasks.
Pricebots: Dynamic Pricing
We propose dynamic pricing algorithms that sellers can use to update the prices of their products online automatically: