Learning to Make Reasonable Assumptions
نویسندگان
چکیده
We describe a general mechanism for the dynamic learning of default assumptions about unknown parameters in a complex problem. We evaluate the mechanism in the context of scheduling an academic conference, utilizing an existing scheduling system. We show that the assumptions help the system find better schedules in the presence of uncertainty, and further that the assumptions aid the system’s elicitaiton procedure.
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