Speaker: Hector Levesque
Professor, Computer Science
Artificial Intelligence: Knowledge Representation and Reasoning
Title: On Our Best Behaviour: Anaphor and the science of AI
The science of AI is concerned with the study of intelligent forms of behaviour in computational terms. But what does it tell us when a good semblance of a behaviour can be achieved using cheap tricks that seem to have little to do with what we intuitively imagine intelligence to be? Are these intuitions wrong, and is intelligence really just a bag of tricks? Or are the philosophers right, and is a behavioural understanding of intelligence simply too weak? I think both of these are wrong. I suggest in the context of question-answering that what matters when it comes to the science of AI is not a good semblance of intelligent behaviour at all, but the behaviour itself, what it depends on, and how it can be achieved. I go on to discuss two major hurdles that I believe will need to be cleared.
Hector Levesque received his PhD from the University of Toronto in 1981. After graduation, he accepted a position at the Fairchild Lab for AI Research in Palo Alto, and then joined the faculty at the University of Toronto where he has remained since 1984. Dr. Levesque has published over 70 research papers, and is the co-author of a 2004 textbook on knowledge representation and reasoning. He is a founding fellow of the AAAI, and was a co-founder of the International Conference on Principles of Knowledge Representation and Reasoning. He was elected to the Royal Society of Canada in 2006 and to the American Association for the Advancement of Science in 2011. He received the IJCAI Computers and Thought Award in 1985 and the IJCAI Research Excellence Award in 2013.
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