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---
title: Artificial Intelligence
categories: Module
---

**NB** This is a living document and will be updated, augmented, and improved
during the semester.

+ See [Lecture Notes](Overview) for learning materials
+ See [Blackboard](https://ntnu.blackboard.com/) for announcements and 
  discussion boards.
+ [Learning Outcomes]()
+ [Reading List]()
+ [Actions2023]() i.e. changes to be made next year


# Practical Information

1.  It is your responsibility to do the exercises you need to do to understand
    the subject and gain experience.
2.  There are some compulsory assignments, but they do not cover the complete
    material that you will need to study.
3.  Attendance is compulsory for most (read all) sessions in the second half
    of the semester (exact date TBA).
    See under compulsory assignments.
4.  Feedback is provided *in class* upon demonstration of own work
    and solutions.  This includes approval of coursework.
5.  The module emphasises a broad and relational understanding, consolidating
    theory, practice (programming), and philosophy (incl. ethics)

## How to work with the module

1.  Read the theory.
2.  Do practical exercises to *test your theoretical understanding*
3.  Evaluate your own solutions and reflect upon
    - what have you learnt from the exercise?
    - what do you yet not know?
3.  Engage in the philosophical questions.  Discuss with your classmates.
4.  Don't try to do a lot of exercises quickly.
    It is better to make sure that you comprehend a few exercises fully,
    and can justify and validate your own reasoning.
5.  Ask Questions.  
    I will generally not repeat material unsolicited, 
    but I am very happy to discuss any question you may have.
4.  Keep a diary.
    Make sure you can refer back to previous ideas and reuse previous solutions.

##  Compulsory Assignments

There will be two compulsory assignments

### Programming and Problem Solving 

For the first five weeks, we will work mainly on search and optimisation
algorithms, including problem solving through programming.
At the end of these weeks, you will have to submit

1. solutions to two selected problems on CodinGame (at least medium
   difficulty) or from [pai-exercises](https://github.com/hgeorgsch/pai-exercises).  
2. an action-reflection note, where you discuss what you have learnt from 
   each program submitted and why the problem/solution is interesting.
1. an action-reflection note, where you discuss what you have learnt from 
   each program submitted and why the problem/solution is interesting
   in view of the syllabus.
   This should be about ½-1 page.
2. solutions to two selected problems on CodinGame (at least medium
   difficulty) or from [pai-exercises](https://github.com/hgeorgsch/pai-exercises).  

*Details will be published later.*
Make sure to put the reflection note *first* in the document, so that it is
easy to find and read.
After submission, you have to show the program working and discuss the
code with me face to face.

**Deadline** TBA
**Deadline** 26 February 11:59pm

If you submit early, please also ask for feedback early.  I shall also
be happy to give feedback twice, but preferably then on different problems.
The purpose of the exercise is to establish an opportunity to discuss
your work, not to fail anyone.

The material must be submitted in BlackBoard and demonstrated in person
one-to-one with the teacher, during the first session after the deadline.
one-to-one with the teacher, usually during the first session after the deadline.
Formative feedback and approval is given face to face.
(In case of absence under mitigating circumstances, it is possible to do
this in a later session.)

**Learning Outcomes** Programming skills.
Knowledge of Fundamental Algorithms.
Problem Solving Competency.

### Literature, Presentation, and Debate 

**Deadline** Declare group and topic by midnight end of Sunday 27 February.

The second compulsory assignment is a verbal presentation or debate.
I prepare a list of [Questions]() or topics, with associated reading
lists.

1.  You select a topic.  You are not limited to the published list.
    If you have an idea on your own, please discuss it with me.
2.  Read the literature and prepare an introduction to the topic.
3.  Present the topic to class, and engage in discussion.

*Details TBA*.
If there is at least a dozen students in he class, this exercise will
be done in pairs.  If the class is smaller, we have to think differently
to cover a sufficient range of topics.

Panel debates is a good format for this exercise, where two students/pairs 
prepare opposing positions on some controversial question. 
More straight-forward topics are also possible, with a single presentation.
Both technical and philosophical papers and topics may occur, but there
will be an emphasis on philosophical questions.

**Compulsory Attendance** not only for you own presentation, but also
when others present.  

**Learning Outcomes**  Ability to read and interpret research papers.
Verbal presentation skills.  Ability to engage in peer discussions within
the discipline.  Awareness of the ethical concerns within AI.


## How does the exam work

1.  Oral Exam.
2.  You get seven minutes to demonstrate the highlights of your
    understanding of the subject.
    *Make a case for the grade you think you deserve.*
3.  The examiner will use the rest of the time for questions to clarify
    and to demonstrate expected breadth and depth.
4.  Note that there are both theoretical, practical, and philosophical
    learning outcomes,
    and the module emphasises the relation between these three.

+ Capacity: 30 candidates
+ [Assessment Guide]() 
 
# Syllabus

The core syllabus consists of

1.  The lectures and taught sessions.
2.  All learning material provided.
3.  TBC Core reading (session numbers may change)
    - Sessions 1-6: Russel & Norvig, Chapters 1-4 + 6
    - Sessions 7-9: Haupt & Haupt, Chapter 1-4
    - Session 10: Russel & Norvig Chapter 19 TBC
    - Sessions 11-13: Russel & Norvig Chapters 16 and 23
    - Session 14: Russel & Norvig Chapters 28-29

Note that the propositional knowledge that you can find well-defined
in the textbooks only forms a part of this module.  We will also 
study the tacit skills of problem solving and the ethical and
philosophical dilemmas of intelligence, artificial or otherwise.
This requires broader reading and more thinking on your part.
A [Reading List]() is provided and will be developed as we go along.