SYMSYS 1 / LINGUIST 35 / PHIL 99 / PSYCH 35
Minds and Machines
Fall 2019
Stanford University

COURSE INFORMATION
Instructor
Dan Lassiter
Assistant Professor of Linguistics
danlassiter
office: 460-102
office hours: Thursday 1:30-2:30PM

Note: Please do not email the instructor except in case of emergency. Contact your TA or course coordinator, or for general administrative or sensitive inquiries use symsys1staff@gmail.com instead.
Course Coordinator
Erica Yoon
ejyoon
office: Cordura Hall (CSLI, 210 Panama St.), rm. 210
office hours: Make appointments on https://ejyoon.youcanbook.me/
Teaching Assistants

Tamara Prstic, tprstic
office hours: Tues 12-1:30
location: 460-040E
Francesca Vera, fvera
office hours: Wed 1-2:30
location: 460-040E
Stephanie Niu, sniu25
office hours: Wed 10:30-12
location: 460-040E
Ciyang Qing, qciyang
office hours: Mon 2:30-4
location: 460-030D
Aileen Luo, cxluo
office hours: Mon 10:45-12:15
location: 90-92H
John Turman, jturman
office hours: Wed 1:30-3
location: 90-92N
Tess Rinaldo, trinaldo
office hours: Tues 1-2:30
location: 460-040E
Aarush Selvan, aselvan
office hours: Thurs 4-5:30
location: 460-040E
Josh Kornberg, jkornberg
office hours: Mon 3:15-4:45
location: 460-040E
Meeting Times Tuesdays and Thursdays 10:30-11:50 am, starting September 24, 2019
plus sections (see below)
Location Cubberley Auditorium
Description An overview of the interdisciplinary study of cognition, information, communication, and language, with an emphasis on foundational issues: What are minds? What is computation? What are rationality and intelligence? Can we predict human behavior? Can computers be truly intelligent? Lectures focus on how the methods of philosophy, mathematics, empirical research, and computational modeling are used to study minds and machines. Undergraduates considering a major in Symbolic Systems should take this course as early as possible in their program of study.

Students must take this course before being approved to declare Symbolic Systems as a major. All students interested in studying Symbolic Systems are urged to take this course early in their student careers. The course material and presentation will be at an introductory level, without prerequisites.
Assignments
There will be weekly assignments due every Friday, starting the second week of class. All assignments will be submitted via Canvas. See the assignment schedule for details.

Sections
Sections meet every week beginning the second week of class, on Monday October 3. They will cover the material presented in the previous week's lectures. Section attendance constitutes 10% of your final grade.
Readings and videos Students should do assigned readings/watch assigned videos in advance of the class for which they are assigned. This is crucial for success in the class, and class discussion will assume prior familiarity with the contents of the videos and readings. Students must submit brief completion checks for reading(s) and/or video(s) by 9 PM on the day before the class for which the readings/videos are assigned.

The readings will be drawn from two sources:
  • Danny Hillis, The Pattern on the Stone, 2nd edition ($13; available in the Stanford Bookstore and the usual alternative sources)
  • PDF documents posted on the website.
All course videos are available in the "Videos" tab in Canvas.
Course contract: electronics in class
By enrolling in "Minds & Machines", you are signing up for the following contract: No laptop computers, smartphones, iPads, or other internet-enabled devices during class meetings. Students should bring a notebook/notepad and pen/pencil to class for note-taking purposes, as well as the course reader or Hillis book as applicable. This contract has been created in response to a large body of educational research demonstrating that laptop and phone use in class is detrimental to learning. We will discuss this research further in the first course meeting.
Grading
The breakdown will be as follows:
  • Weekly assignments: 55%
  • Reading and video completion checks: 5%
  • Take-home final: 30%
  • Section attendance: 10%

Late policy. For weekly quizzes: Every student gets two penalty-free late days total for the quarter, where a day is charged for lateness between 0 and 24 hours after the time the assignment is due. (This does not include the final, which cannot be submitted late.) After the two late days are used, a penalty of 25% per day off of the total score will be charged, based on the timestamp of the submitted assignment, e.g. an assignment with a score of 100 turned in 24 hours and 1 minute late after both free late days have been used up will be given a score of 50 for grading purposes.
For reading/video completion checks: (1) completion checks will be accepted only until the deadline (Tues/Thurs 10 am before each class), and you won't be able to make your submissions after that time (i.e., late submission is not possible); (2) we will forgive TWO missing completion checks. So if you have three missing checks in total, we will omit the first two from your grade calculation but you will lose points for the third missing one.

Students with Documented Disabilities
Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE).  Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is being made. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations.  The OAE is located at 563 Salvatierra Walk (phone: 650-723-1066, URL: http://oae.stanford.edu).
Collaboration & plagiarism policy
All work submitted should be exclusively your own. You may discuss homework questions verbally, but you may not share any written documents pertaining to homework questions, including emails, draft answers, etc.

You should also consult Stanford's plagiarism policy carefully. If you use ideas from someone else, you should cite a source. If you use someone else's words, you should indicate this by using a quotation and citing a source.

Failure to follow the plagiarism policy is a serious offense and can lead to major sanctions, including failing the class and official sanctions through the Office of Community Standards.
Schedule
Date
Topic
Required preparation & assignments
Extras Lecture
slides
Tues.
9/24

(Reverse-)engineering human intelligence

(fun) The Robots are Winning
(serious) Laptops in class: [one] [two] [three] etc. etc.
[Slides]
Thurs.
9/26

Bodies, Minds, and Machines  


[Slides]
Tues.
10/1

From embodied to abstract machines

[Slides]
Thurs.
10/3

Machines for natural language grammar

[Slides]
Tues.
10/8

The computational theory of mind

[Slides]
Thurs.
10/10

Computation & brains

Can Neuroscience Understand Donkey Kong, Let Alone a Brain? [Slides]
Tues.
10/15

Levels of analysis

[Slides]
Thurs.
10/17

Intuitive theories
(Guest: Tobi Gerstenberg)

[Slides]
Tues.
10/22

Machine learning & human learning

Background video: Probability [Slides]
Thurs.
10/24

Bayesian models of cognitive development

A tutorial introduction to Bayesian models of cognitive development [Slides]
Tues.
10/29

Reasoning

[Slides]
Thurs.
10/31

Perception

Tues.
11/5

Choice & action

[Slides]
Thurs.
11/7

Neural networks 1

"Deep learning: A philosophical introduction" [Slides]
Tues.
11/12

Neural networks 2

[Slides]
Thurs.
11/14

Cutting-edge deep learning
(Guest: Richard Socher)

Week 8 Quiz (due Nov. 15 at 5 PM)
Tues.
11/19

Agents in interaction

[Slides]
Thurs.
11/21

Natural language pragmatics

[Slides]
Tues.
12/3

Social cognition & pragmatics

"Universal social cognition" "Pragmatic language interpretation as probabilistic inference"
Thurs.
12/5

Review & discussion

Take-home final released
Thurs.
12/12
Take-home final due at noon