Uncertainty in AI Seminar

Winter 96-97

BGU Math & Computer Science Department

Description of the course

The course will consist of an introduction to the course topics, followed by student talks on selected papers. The outline of the first part of the course is as follows.

  1. Introduction
  2. Evidential (probabilistic) reasoning
  3. Other formalisms
  4. Applications

Reading List

  1. "Probabilistic Reasoning in Intelligent Systems", Judea Pearl, Morgan Kaufmann
  2. "Readings in Uncertain Reasoning", Shafer and Pearl, Morgan Kaufmann
  3. Articles from the uncertainty in AI community, and related papers.

Requirements and Prerequisites

This course is predominantly for graduate students, but senior year (3rd year or above) CS students may also attend. Atttendance of all classes, or an equivalent replacement, is mandatory. One 2-hour talk on a set of articles from the reserach literature will be prepared and presented by each student.

Administrative Issues

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