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"Humans make hundreds of routine decisions daily," explains Professor Amy Greenwald of Brown University's Department of Computer Science (Brown CS). "More often than not, the impact of our decisions depends on the decisions of others. As AI progresses, we're offloading more and more of these decisions to artificial agents. My research is aimed at building AI agents that make effective decisions in environments inhabited by both human and artificial agents."
On July 18, Amy gave a keynote address ("The Interplay of Agent and Market Design") at Microsoft's Faculty Summit 2017 ("The Age of AI"). The event, now in its eighteenth year, brings together thought leaders and researchers from a broad range of disciplines, including computer science, the social sciences, human design and interactions, and policy. This year's goal was to highlight some of the key challenges posed by artificial intelligence and identify the next generation of approaches, techniques, and tools that will be needed to develop AI to solve the world’s most pressing challenges.
In her talk, Amy explained how current efforts in building AI agents have become increasingly relevant to economic domains, mostly in the service of perfecting market designs. She explained a mathematical connection between auctions and contests, and then observed that productivity can be maximized by rewarding not only the very best submissions, but rather by promising to reward any one of the top (for example) quarter of the submissions. She also discussed the importance of inverse reinforcement learning to market design, where the goal is to extract underlying motivations from agent behaviors. She concluded by touching on AI agent design in applications, ranging from renewable energy markets to online ad exchanges to wireless spectrum auctions.
You can watch a video recording of Amy's keynote here.
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