October 2, 2017
The project by Prof. Jin Tian seeks to develop a sound and general causal inference framework for decision-making of intelligent systems, including (1) learning a causal representation of the data-generating environment (learning), (2) performing efficient inference leveraging the learned model (planning/inference), and (3) using the inferred representation to decide how to act next (decision-making). The work is collaborative with Dr. Elias Bareinboim at Purdue University and Dr. Judea Pearl at UCLA.
For more information, please to go to:
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1704352