Keywords: multi-agent systems, autonomous agents, auctions, mechanism design, algorithmic game theory, evolutionary algorithms, bargaining, sponsored search, display advertising, financial markets, algorithmic trading, the smart grid, electric vehicle charging.
My research is in the area Artificial Intelligence and with a focus on Multi-Agent Systems. Multi-agent systems consist of intelligent, automous software programs, called agents, interacting with one another and performing some predefined tasks. These agents typically act on behalf of, and can interact with, individual people. Good examples are bidding agents in auctions such as eBay, sponsored search and display advertising, and autonomous trading agents in financial markets. More recently, the smart grid has emerged as a natural application domain for multi-agent systems, and this is one of the application areas for my research as well.
A particular area of expertise is mechanism design, which uses the principles of game theory to incentivese people (or, in my research area, agents) to behave in a certain way. Mechanism design is also known as reverse game theory: whereas game theory seeks to predict how agents behave (or prescribe how rational agents should behave), the aim of mechanism design is to design the rules of the game such that desirable outcomes are achieved. To make this more specific, many situations, commonly known as the tragedy of the commons, lead to an equilibrium where resources are depleted when everyone acts rationally and in their self interest. This is an undesirable outcome for everyone involved. Mechanism design then asks whether we can design incentives, e.g. in the form of payments and taxes, that change the equilibrium of the game to a more desirable outcome, even if everyone remains self-interested. The main application area for my research is in the design of auction mechanisms, such as those used in financial markets.
For more information about my specific research areas, check out my research page in the menu on the left.