b. 1962
Craig Boutilier is a Canadian computer scientist and AI researcher specializing in decision theory, reinforcement learning, and computational models of rational agency. His work bridges philosophy of action, game theory, and artificial intelligence, particularly in formalizing belief revision and sequential decision-making under uncertainty.
Pioneered work on qualitative decision theory and preference elicitation
Developed influential models of belief revision in dynamic and sequential contexts
Advanced computational approaches to Markov decision processes and reinforcement learning
Contributed foundational work on multi-agent systems and game-theoretic reasoning
Principal Scientist at Google Research, leading work on recommender systems and AI