Learning and Planning in the Data-to-Deployment Pipeline
With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems. I focus on the problems of public health and wildlife conservation, and address one key cross-cutting challenge: how to effectively deploy our limited intervention resources in these problem domains. I present our deployments from around the world as well as lessons learned that I hope are of use to researchers who are interested in AI for Social Impact. Achieving social impact in these domains often requires methodological advances. I will highlight key research advances in topics such as computational game theory, multi-armed bandits and influence maximization in social networks as well as in integrating machine learning with such advances in the data to deployment pipeline. In pushing this research agenda, our ultimate goal is to facilitate local communities and non-profits to directly benefit from advances in AI tools and techniques.
About the Speaker:
Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research in Computation and Society at Harvard University; concurrently, he is also Director "AI for Social Good" at Google Research India. He is a recipient of the IJCAI John McCarthy Award, ACM/SIGAI Autonomous Agents Research Award from AAMAS, AAAI Robert S Engelmore Memorial Lecture award, INFORMS Wagner prize, Rist Prize of the Military Operations Research Society, Columbus Fellowship Foundation Homeland security award, AAMAS influential paper award, best paper awards at conferences such as AAMAS, IJCAI, IVA, and meritorious commendations from agencies such as the US Coast Guard and the Los Angeles Airport. Prof. Tambe is a fellow of AAAI and ACM.
Host: Madhav Marathe