Last updated: 28 January 2019

Home Page for CM50230 & CM30229
Intelligent Control & Cognitive Systems   2019

Dr. Joanna Bryson

Dr. Wenbin Li

This unit reflects a rapidly developing field.  Therefore the schedule on this page is always subject to change.

This course has three different but complementary objectives (see unit descriptions):
  1. To give students skills and experience in constructing intelligent systems.
  2. To provide an academic survey concerning the roles and capabilities of cognition in both nature and artefacts.  The goal of this survey is that students should become conversant in the topics, be able to research and provide advice for companies, organisations, or citizens that ask for their help or opinion, and able to seek out, acquire, and/or engage with expertise on these topics.
  3. To give students skills and experience in reading and writing academic reports and communication.  This should be of benefit for writing dissertations.  For CM50230, the level of skill in writing should extend to a capacity for submission for publication in workshops or conferences.

Because this course is about a topic that is both central to human identity, and also disrupting the global economy, much of its content is necessarily a matter of controversy.  For this reason the material is presented with a strong component of history of science. This allows you as students to understand and evaluate the biases not only of the lecturer, but also of other academics you may read.  Bias is an intrinsic part of intelligence (as you'll learn in this course); the question is how to best cope with it.  This course is consequently also about how academics and societies arrive at a set of material which we present to students and use in policy.  Societies and universities are also cognitive systems, so this course is about itself, and about your degree.

This unit is taught flipped classroom. This is partially in response to student reviews from the first five years, where students wanted more time to go over the lectures and to ask questions.  It is also in response to the fact that the lecturer lives on a different continent. Most weeks there are two lectures to watch, generally on video, plus one quiz and one live discussion session. The time for the quiz & the discussion session add up to one additional hour.  Some weeks there is only one video and one live tutorial for the coursework, or one or two live lectures where the video needs to be updated.

To make sure that everyone is keeping up with the videos, there are quizzes. These are on moodle but at a fixed time, generally at the beginning of the lecture discussion session.  The quizzes do not count for much of your mark, and you will drop your worst two (of seven) of your marks.  They substantially improved performance on the final exams since the year we introduced them.

This page is provided as a resource, mostly so you can find lecture notes and problem sets.  There is also a moodle page associated with this course, which contains forums for support & is where you submit your coursework.  You are responsible for reading thoroughly all communication from email, the moodle news forum, and the coursework specifications.

Note on Labs:  Labs start in the first week, but not before the first lecture; those with the lab before the first lecture should attend another lab first week.  In general you are welcome to attend labs other than your assigned one, but the people who are assigned to a lab have first precedence for equipment and tutor time.
Note on Quizzes:  Quizzes start in the second week, you will be marked on your best 5 of 7. They are (mostly) held at the beginning of lecture, those not attending a lecture cannot take that week's quiz.  Because of logistics, two quizzes will be conducted without this restriction.

Week
 Lecture Topics
(exact organization still subject to change)
Coursework & Labs
(courseworks due Friday at midnight, handed out Tuesdays in Lecture)
First Lecture
Special notes
1
Introduction, Intelligence & Sensing; Artificial Intelligence & Cognition.
Lecture 1; Lecture 2
Coursework 1  handed out. 4 Feb Don't miss the first lecture! Don't miss your first lab! 
No quiz this week.
2
Action Selection; Cognitive Architectures.
Lecture 3; Lecture 4
Thursday quiz: 1-3
Robots handed out in lab
11 Feb
This is a bunch of history, but it's very relevant to your first lab as you think about the achitecting your robots' mind.
3
Perception; Learning and Evolution.
Lecture 5; Lecture 6
Coursework 4 (MScs only) handed out.
Thursday quiz: 4-6
18 Feb
We won't use learning much in the labs, but we need to understand how it's used in Nature, and how it should inform our Design.
4
Evolvability, Learnability, and Design–Perception for Robots; Science, Agents and Spatial Simulations
Lecture 7; Lecture 8
Coursework 1 Due Thursday.
Coursework 2   handed out.
No quiz or q&a
NetLogo lecture live Friday (by Holly?)
25 Feb
More advanced tips from Nature on learning to learn; then moving on to thinking about cognition as a social process.
Quiz is just on learning, evolution, and design, not on agents or science.
5
Social Simulation and Social Structure. NetLogo
Lecture 9; Lecture 10;

Thursday quiz: 7-9
Netlogo labs this week & next.


4 Mar
How AI can be used to understand intelligence in nature; then moving on to thinking about cognition as a social process.
No quiz this week.
6
Hypothesis Testing and Evidence; 
Multiple Conflicting Goals: Intro to Game AI BUNG and ABOD3 
Lecture 11; Lecture 12
; Lecture 14

Game AI lecture live Friday by Wenbin
12 Mar
This week makes sure you have what you need to write up your CW2, and then introduces the concepts for CW3. Quiz is on science and social simulations, not game AI and hypothesis testing, but will discuss this week's lectures in flipped classroom Tuesday, especially multiple conflicting goals because that leads into ethics.
No quiz this week.
7
Likeability, Believability & Engagement
Lecture 13

Game AI labs this week & after break
Coursework 2 due Monday

Thursday quiz 11-13 Coursework 3 handed out
18 Mar
The lectures for Game AI also bridge you into human-like behaviour, which will be core for thinking about ethics. Who do you put first, yourself or your team's goals? There's no simple answer.
 


Consolidation


8
Culture, Language & Cognition: I & II
Lecture 15 & 16 (double lecture)

Thursday quiz 15, 16
1 Apr
Regular lectures, not video!  Quiz after Friday's lecture. Language bridges between social cognition, learning, and is core to human ethics.
9
Emotions & Intelligence; Mind & Consciousness
Lecture 17; Lecture 18
Code for Coursework 3 due Monday.
Labs mandatory!
Thursday quiz 17 & 18

8 Apr
Lab: Round-robin game competition; if you can't make your lab you need to get someone else to make your code run for you (NOT the tutors!)
(Video) lectures (with normal quiz Tuesday quiz postponed a week because no appropriate room available, see below) take a functionalist, empirical, science-driven perspective on topics critical to human society and ethics, in preparation for considering AI's role in ethics.
10
Ethics & Society; Politics & Regulation
Lecture 19; Lecture 20
Coursework 3 writeup due Monday
Thursday quiz, 19 & 20
15 Apr
Regular lectures, not video! (But one was previous week.)  This material probably affects your coursework least, but your career (and life) most, of any of the lectures. 


Spring Break


Rev
Revision Week
(revision lecture Thursday)
Beauty Competition in Friday's lecture slot.
Robots must be disassembled by this week.
Unless they win the beauty competition!

6 May

Coursework 4 due for postgraduates.

If you want to meet with Dr. Bryson privately, schedule an appointment during her office hours; if there are none coming up, email her.  Please don't email lecturers or tutors questions about lectures, course content, or coursework – use Moodle!  Questions are good work done by good students, both they and answers belong to the whole course and should appear in the Moodle forums.  It's also easiest to get our attention in lecture, lab and the moodle forums.  Note that extension requests go to your Director of Studies, not to Lecturers.  The best time to talk to Dr. Bryson is often immediately after lecture (before is OK iff everything technical seems to be set up, NOT if she is fiddling with her laptop. This goes for TAs too, not just students!)

Is there a text?

This is an advanced course for which there is (so far) no single text book.  One of the skills taught in this course is reading primary literature–that is, you should be able to read some of the publications cognitive scientists use to communicate to each other.  However, we have also ordered a large number of books on robots, AI, LEGO robots & Cognitive Science for the library.  Have a look on the shelves or in the catalogue.  Let the lecturers know if you particularly like any of these books and/or think we should get more copies.



page author: Joanna Bryson