The “Nobel Prize in Computing” was awarded to Pearl for his advances in probabilistic and causal reasoning. His work has lead to the development of thinking machines that can cope with uncertainty and can make decisions even when answers aren’t black or white.
The UCLA computer science professor created the term “Bayesian Network,” which refers to a statistical model ACM describes as mimicking “the neural activities of the human brain, constantly exchanging messages without benefit of a supervisor.”
Bayesian networks have been used to look at biological data for studies of medicine and diseases.
He was born in Tel Aviv in 1936 and earned degrees from Technion in Israel, Rutgers University and the Polytechnic Institute of Brooklyn.
Recently he has been studying the idea of computers and morality. He joined UCLA in 1970 and directed the school’s Cognitive Systems Laboratory.
He is well known for his best seller Heuristics, Probabilistic Reasoning in Intelligent Systems and Causality: Models, Reasoning, and Inference.