Class information

• Lecturer: Jun Otsuka ([email protected])
• Day&Time: Monday 10:30-12:00
• Room: 新7講
• Office hour: Tuesday 10:30-12:00 or by appointment
• PandA: https://panda.ecs.kyoto-u.ac.jp/portal/site/2023-101-5131-004

授業の概要・目的

This advanced course will explore in depth a range of topics in the recent studies on causality both in philosophy and machine learning. We will examine three major philosophical theories of causation, namely (1) the causal Bayes nets, (2) the process theory, and (3) the interventionist theory, focusing especially on their mathematical/formal underpinnings.

到達目標

By the end of this course, students will be able to:

• Understand and critically evaluate a range of philosophical theories of causation
• Understand the basics of mathematical theories used to model causality, including Bayesian networks, monoidal categories, and monoid actions.

授業計画と内容

1. 4/10 Orientation
2. 4/17 Causality: relationship or process?
   • Reading: Kutach Ch. 2 (& 3)
3. 4/24 Regularity & Probability
   • Reading: Kutach Ch. 6
   • Optional: 大塚 23-32, Pearl 7-24