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Course structure and connection to textbook

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This information will be updated as the semester progresses.
Note that the lectures provide the best guide of what is the most appropriate reading material.

This page is for information purposes only.
The lecturers can change the contents of the actual material covered in class.

Section 1 - Introduction and Intelligent Agents

• Introduction (0.5 lecture)
  • Chapter 1 of textbook
• Intelligent Agents (1 lecture)
  • Chapter 2 of textbook
• Universal Artificial Intelligence (0.5 lecture)
  • Based on book Hutter (2005) http://www.hutter1.net/ai/uaibook.htm
• AI: Philosophical Foundations (0.5 lecture)
  • Chapters 26 and (partially) 27 of textbook

Section 2 - Search

• Introduction (0.5 lecture)
• Uninformed search (0.5 lecture)
• Informed search (2 lectures)
• Local search (1 lecture)
• Adversarial search (2 lectures)

Section 3 - Knowledge Representation

• Propositional logic (2 lecture2)
  • Chapter 7 of textbook
• First-order logic (1 lecture)
  • Chapter 8 of textbook
• Inference in first-order logic (1 lecture)
  • Chapter 9 of textbook
• Constraint satisfaction problems (2 lectures)
  • Chapter 5 of textbook

Section 4 - Planning

• Overview of planning (1 lecture)
  • Chapter 11.1 of textbook
• Planning with state-space search (1 lecture)
  • Chapter 11.2 of textbook
• Partial-order planning (1 lecture)
  • Chapter 11.3 of textbook
• Planning graphs (1 lecture)
  • Chapter 11.4 of textbook
• Planning with propositional logic (1 lecture)
  • Chapter 11.5 of textbook
• Extensions of classical planning (1 lecture)
  • Chapter 12 of textbook

Section 5 - Learning

• Overview of machine learning (0.5 lecture)
• Decision trees (1.5 lecture)
  • Chapter 18.3 of textbook
• Neural networks (2 lectures)
  • Chapter 20.5 of textbook
• Bayes nets (2 lectures)
  • Chapter 14.1 -- 14.4

Section 6 - Overview of Other AI Areas

• Perception, robotics, natural language processing

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