Simulating Language

Academic year 2020-2021

This is the webpage for the Honours/MSc course Simulating Language, running in academic year 2020/2021. We will add links to materials (readings, videos, code) to this page; you will need to use Learn for electronic submission of your assessed work, and to keep an eye out for any course announcements.

Course summary

In this course we are going to be using simulation models to study language. People use various types of models in linguistics for a number of purposes; in this course we are going to focus using models to study how processes of learning, communication and evolution shape linguistic systems, and we’ll primarily be using agent-based Bayesian models (don’t worry, we’ll explain what that means!).

This is a practical course: you’ll be running and tinkering with code for computational models written in python. You don’t need to be programmer to take the course - no programming knowledge is assumed, and we are doing everything in the simplest way we can think of, building from the ground up. But you will be doing stuff with code, so you have to be prepared to give it a go, dive in, and try stuff out. Don’t worry, we’ll help you figure it out.

The teaching team

Simon Kirby, Kenny Smith and Matt Spike are the main lecturers and lab demonstrators - the best way to get in touch with us is in one of the drop-in lab sessions, see below, or by messaging on Teams. In the drop-in labs we’ll be assisted by Claire Graf, Annie Holtz and Henry Conklin.

Structure of the course

Each week there is a set reading (which you do in your own time), a lecture (live on Teams), and then a programming practical (which you attempt in your own time, and get help with in the drop-in labs).

Readings

The week-by-week reading content is at the bottom of this page. The readings consist of our notes plus a mix of journal papers and book chapters. For some weeks also have associated quizzes or mini-tests so you can evaluate your own understanding.

For some of the lectures the reading is flagged up as being pre-reading, i.e. we will assume you have done this preparatory work prior to the lecture and will design the lecture accordingly (i.e. we might refer to stuff in the preparatory materials or ask you questions about it).

You should always complete the reading materials and attend/watch the lecture before attempting the programming practical or attending the drop-in lab classes - the practicals involve playing with models that implement the ideas covered in the readings and lecture recordings, so will make a lot more sense when you have that context.

Each week there is a designated academic lead, who sets the readings and presents the lecture - if you have content questions on a given week, the academic lead for that week should be one of your points of contact, but we are all familiar with all of the content so anyone you see at drop-in labs should be able to help!

Lectures

Lectures start in week 2, i.e. the first lecture is Tuesday 19th January. Lectures will be recorded and appear on Teams, so if you can’t attend (e.g. due to timezone) then you will be able to see what was said.

Practicals and drop-in labs

You can attempt the programming practical on your own, but we will be providing drop-in labs at set times each week where you can come and get our help to figure out problems. You should come to the drop-in labs if you need help with a specific problem, but you are also welcome to just turn up in drop-in labs to hang out and work through things on your own with us in the background - some people find that having set times helps them focus.

You will be assigned a lab group that will take place at one of the following times in weeks 2-11:

The drop-in labs happen on gather.town. You will be assigned a lab time and a tutor during week 1, and you can find a link to gather.town from your lab group channel on Teams. You can drop in at any time during your session and ask questions, get help with the programming practicals, or just hang out. You can come as much or as little as you want: we’ll be sad if we never see you, but you’ll probably be sad if you see us too much.

Chat on Teams

In addition to asking questions in lectures and drop-in labs, we will set up channels on Teams for you to ask questions. If you have a question that you can’t ask live, Teams (rather than email) is our preferred way for you to get in touch.

Assessment

The two assignments involve a mix of practical work and written sections and have the following deadlines:

The assignments will be available to start working on after the last lab that relates to the content being assessed. This will usually be two weeks in advance of the deadline.

Course Materials

Week 1 (commencing 11th January): No class

But make an early start on the reading and preparatory materials for weeks 2 and 3 - note that for week 3 in particular there’s a fairly chunky bit of preparatory work.

Week 2 (commencing 18th January): Introduction

Lead: Kenny Smith

Week 3 (commencing 25th January): Concept learning

Lead: Kenny Smith

Week 4 (commencing 1st February): Frequency learning and regularisation

Lead: Kenny Smith

Week 5 (commencing 8th February): Iterated Learning

Lead: Simon Kirby

Free week (commencing 15th February): No classes

Catch up, read ahead, start the first assessment, or have a rest.

Week 6 (commencing 22nd February): Communication and the RSA model

Lead: Kenny Smith

Week 7 (commencing 1st March): Compositionality

Lead: Simon Kirby

Week 8 (commencing 8th March): Hierarchical models and learning the prior

Lead: Kenny Smith

Week 9 (commencing 15th March): Innateness and culture

Lead: Simon Kirby

Week 10 (commencing 22nd March): Adding biological evolution to our models

Lead: Simon Kirby

Week 11 (commencing 29th March): This view of language

Lead: Simon Kirby

Re-use

All aspects of this work are licensed under a Creative Commons Attribution 4.0 International License.


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