On Friday April 22nd, we will have a joint LogiCIC/LIRa session with Jon Williamson. Everyone is cordially invited!
Speaker: Jon Williamson (University of Kent)
Date and Time: Friday, April 22nd 2016, 13:00-14:30
Venue: Science Park 107, Room F1.15
Title: Inductive Logic for Automated Decision Making.
Abstract. According to Bayesian decision theory, one’s acts should maximise expected utility. To calculate expected utility one needs not only the utility of each act in each possible scenario but also the probabilities of the various scenarios. It is the job of an inductive logic to determine these probabilities, given the evidence to hand. The most natural inductive logic, classical inductive logic, attributable to Wittgenstein, was dismissed by Carnap due to its apparent inability to capture the phenomenon of learning from experience. I argue that Carnap was too hasty to dismiss this logic: classical inductive logic can be rehabilitated, and the problem of learning from experience overcome, by appealing to the principles of objective Bayesianism. I then discuss the practical question of how to calculate the required probabilities and show that the machinery of probabilistic networks can be fruitfully applied here. This culminates in an objective Bayesian decision theory that has a realistic prospect of automation..