COMP219 - Artificial Intelligence

Lecturer

Dr. Frans A. Oliehoek
Room 222, Ashton Building
Email: frans.oliehoek@liverpool.ac.uk

Demonstrators

Joe Collenette - sgjcolle@student.liverpool.ac.uk
Gregory Palmer - G.J.Palmer@liverpool.ac.uk
Pavithra Rajendran - Pavithra.Rajendran@liverpool.ac.uk

Lectures

In general, these are the times:

Monday, 16:00-17:00, CTH-LTA.
Tuesday, 10:00-11:00, REN-LT6.
Friday, 11:00-12:00, CHAD-CHAD.

There is a revision lecture scheduled for Wednesday 10th Jan (10am in CHAD-CHAD).

Class Tests

There will be two class tests.

Class test 1 (Prolog)
Friday 17th November (Week 8), 15:00-17:00.
Class test 2 (everything but Prolog)
Friday 15th December (Week 12), 15:00-17:00.

The class test will take 1h.

Location of class test 2

The 2nd class tests is split over two venues, depending on what letter your last name starts with you should report to one of these:

CHAD-ROTB: A-G
CTH-LTA: H-Z

Reading Lists and Learning Resources

The following AI textbook is highly recommended:

S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 2010 (3rd edition).

(It is frequently, and with reason, referred to as the bible of AI). Other options are:

E. Rich and K. Knight. Artificial Intelligence. McGraw-Hill, 1991 (2nd edition).
A. Cawsey. The Essence of Artificial Intelligence. Prentice-Hall, 1998.

For the prolog part, I recommend:

I. Bratko. Prolog Programming for Artificial Intelligence. Addison Wesley, 1990.

This is a really well-written book. Another options is:

Sterling, Leon, and Ehud Y. Shapiro. The art of Prolog: advanced programming techniques. MIT press, 1994.

In addition to these books, the lecture notes below, give a complete overview of the treated topics.

Lecture Notes 2016

Note:

Due to scheduling constraints, not all lecture will be given in the below order.
Below are last year's notes and are still subject to (minor) revisions.
The final notes used this year will be posted further below...

Lectures will cover the following topics:

Lecture 1 - Introduction. [Slides] [Slides (4 per page)]
Lecture 2 - AI Problems and Applications. [Slides] [Slides (4 per page)]
Lecture 3 - Introduction to Prolog. [Slides] [Slides (4 per page)]
Lecture 4 - Intelligent Agents. [Slides] [Slides (4 per page)]
Lecture 5 - Search. [Slides] [Slides (4 per page)]
Lecture 6 - Recursion in Prolog. [Slides] [Slides (4 per page)]
Lecture 7 - Search Strategies. [Slides] [Slides (4 per page)]
Lecture 8 - Combining Search Strategies and Speeding Up. [Slides] [Slides (4 per page)]
Lecture 9 - Lists in Prolog. [Slides] [Slides (4 per page)]
Lecture 10 - Heuristic Search. [Slides] [Slides (4 per page)]
Lecture 11 - Search in Complex Environments. [Slides] [Slides (4 per page)]
Lecture 12 - Prolog - Cut. [Slides] [Slides (4 per page)]
Lecture 13 - Game Playing. [Slides] [Slides (4 per page)]
Lecture 14 - Knowledge Representation. [Slides] [Slides (4 per page)]
Lecture 15 - Prolog - Negation as Failure. [Slides] [Slides (4 per page)]
Lecture 16 - Forward and Backward Chaining. [Slides] [Slides (4 per page)]
Lecture 17 - Semantic Networks. [Slides] [Slides (4 per page)]
Lecture 18 - Expert Systems and Ontologies. [Slides] [Slides (4 per page)]
Lecture 19 - Logic for KR. [Slides] [Slides (4 per page)]
Lecture 20 - Propositional Reasoning. [Slides] [Slides (4 per page)]
Lecture 21 - Propositional Resolution. [Slides] [Slides (4 per page)]
Lecture 22 - First-Order Resolution. [Slides] [Slides (4 per page)]
Lecture 23 - Classical Planning. [Slides] [Slides (4 per page)]
Lecture 24 - Scheduling in Real World Planning. [Slides] [Slides (4 per page)]
Lecture 25 - Supervised Learning. [Slides] [Slides (4 per page)]
Lecture 26 - Linear Models and Non-parametric Models. [Slides] [Slides (4 per page)]
Lecture 27 - Reinforcement Learning. [Slides] [Slides (4 per page)]

Lecture Notes 2017

This year's slides:

Lecture 1 - Introduction. [Slides] [Slides (4 per page)]
Lecture 2 - AI Problems and Applications. [Slides] [Slides (4 per page)]
Lecture 3 - Introduction to Prolog. [Slides] [Slides (4 per page)]
Lecture 4 - Intelligent Agents. [Slides] [Slides (4 per page)]
Lecture 5 - Search. [Slides] [Slides (4 per page)]
Lecture 6 - Recursion in Prolog. (Given as the 5th lecture) [Slides] [Slides (4 per page)]
Lecture 7 - Search Strategies. [Slides] [Slides (4 per page)]
Lecture 8 - Combining Search Strategies and Speeding Up. [Slides] [Slides (4 per page)]
Lecture 9 - Lists in Prolog. (Given on Friday 20-10-2017) [Slides] [Slides (4 per page)]
Lecture 10 - Heuristic Search. [Slides] [Slides (4 per page)]
Lecture 11 - Search in Complex Environments. [Slides] [Slides (4 per page)]
Lecture 12 - Prolog - Cut. (Given on Tuesday 24-10-2017) [Slides] [Slides (4 per page)]
Lecture 13 - Game Playing. [Slides] [Slides (4 per page)]
Lecture 14 - Knowledge Representation. [Slides] [Slides (4 per page)]
Lecture 15 - Prolog - Negation as Failure. (Given on Tuesday 10-11-2017) [Slides] [Slides (4 per page)]
Lecture 16 - Forward and Backward Chaining. [Slides] [Slides (4 per page)]
Lecture 17 - Semantic Networks. [Slides] [Slides (4 per page)]
Lecture 18 - Expert Systems and Ontologies. [Slides] [Slides (4 per page)]
Lecture 19 - Logic for KR. [Slides] [Slides (4 per page)]
Lecture 20 - Propositional Reasoning. [Slides] [Slides (4 per page)]
Lecture 21 - Propositional Resolution. [Slides] [Slides (4 per page)]
Lecture 22 - First-Order Resolution. [Slides] [Slides (4 per page)]
Lecture 23 - Classical Planning. [Slides] [Slides (4 per page)]
Lecture 24 - Scheduling in Real World Planning. [Slides] [Slides (4 per page)]
Lecture 25 - Supervised Learning. [Slides] [Slides (4 per page)]
Lecture 26 - Linear Models and Non-parametric Models. [Slides] [Slides (4 per page)]
Lecture 27 - Reinforcement Learning. [Slides] [Slides (4 per page)]

Labs

NOTE: the schedule for the labs is still subject to change!

Labs will start in Week 3, and will end after Week 6. You will be assigned one of the following three lab sessions. Please check your timetable to know when/where your lab is.

The exercises to be carried out during the lab sessions (one in each week):

Lab Exercise 1: to be carried out during week 2. [Instructions] [familyTree.pl]
Lab Exercise 2: to be carried out during week 3. [Instructions] [monkey.pl]]
Lab Exercise 3: to be carried out during week 4. [Instructions]
Lab Exercise 4: to be carried out during week 5. [Instructions] [nqueens2.pl]

In order to download the .pl files, please right-click and select 'save link as'. Alternatively, you can download all lab resources in a [zip file].