Introduction to Cognitive Science

SYMSYS 100 / PSYCH 035 / LINGUIST 144 / PHIL 190
Winter 2013
Tuesdays & Thursdays, 14:15 - 15:30
Room 420-040 (Jordan Hall, basement)

Instructor
Noah Goodman (email) Office hours: TBA Office: 420-356 (Jordan Hall)
Teaching Assistants
Ben Holguin (email) Section 60939 Thursday 1:15-2:05pm Bldg 200, Room 107 Office hours: Tuesday 4-5 460-40	Dasha Popova (email) Section 60690 Thursday 5:15-6:05pm Bldg 160, Room 318 Office hours: Friday 9-10 460-30e	Jean Wu (email) Section 60940: Wednesday 4:15-5:05pm Bldg 200, Room 107 Office hours: Wednesday 11:15-12:15 Location Gates 232
Contact
This piazza site will be used for reading responses, discussion, and questions. Please post questions about homework and class content here. To email the entire staff, please use the following address: [email protected].
Assessment
Four homework assignments 50% HW will be assigned on Fridays and due the following Friday at 5:00pm. Late submissions will not be accepted unless by prior arrangement with a TA. (See the policy below.)	Weekly reading responses 40% Each week students from one class section will post short (2-3 paragraph) responses to the readings on piazza; the remaining students will comment on these responses. (See section assignments below.)	Class participation 10% Class participation includes lecture and section participation.
Assignments
Homework Homework 1 TM.py Homework 2 cfg.py Homework 3, nn.pyc, hw3.py Homework 4
Reading responses Each week, students from one section post short responses to the readings for the upcoming week, by Sunday (midnight). The rest of the class responds to/comments on the initial responses by class on Tuesday (2:15pm). Ben's section: posting initial responses by 1/13, 2/3, 2/24 Dasha's section: posting initial responses by 1/20, 2/10, 3/3 Jean's section: posting initial responses by 1/27, 2/17, 3/10
Late Assignment Policy Each student gets one day (24 hr) of extension to be used on any one of the four homework assignments without penalty. If you need additional late days, there will be a 10% penalty per 24 hrs, and no assignment will be accepted more than two days (48 hrs) after its due date. For the (primary) reading responses, we will deduct 1 point per late day (each response is worth 3 pts.)

Schedule
1/8	Course Introduction	1/10	Computation and intelligence Lecture Slides Readings: Miller (2003), The Cognitive Revolution: A Historical Perspective (pdf) Marr (1982), Vision, Chapter 1: The Philosophy and the Approach (pdf)
1/15	Thomas Icard: Turing Machines Lecture Slides Readings: Turing Machines and Computability (Chapter 22 from this textbook. Chapter 23 optional.) Reading responses this week: Ben's section (others comment).	1/17	Lambda Calculus, and the Church-Turing Thesis Lecture Slides Readings: Turing (1950), Computing Machinery and Intelligence (pdf) The Church-Turing Thesis. Lambda calculus. HW 1 assigned tomorrow.
1/22	Cognitive Architecture Readings: Newell (1980), Physical symbol systems. Reading responses this week: Dasha's section (others comment).	1/24	Mehran Sahami: Classical AI (Lecture Slides) Readings: A. Newell, J.C. Shaw, and H. Simon (1958), Report on a General Problem-Solving Program. The Chinese Room Argument. [Optional: Nils Nilsson (2005), Human-Level Artificial Intelligence? Be Serious!] HW 1 due tomorrow.
1/29	Daniel Lassiter: Chomsky and the Language Wars (Lecture Slides) Readings: John Searle (1972), Chomsky's Revolution in Linguistics. R. Allen Harris (2010), Chomsky's Other Revolution. Reading responses this week: Jean's section (others comment).	1/31	Chris Potts: Semantics Lecture Slides Readings: David Lewis (1970). General semantics. [Required: sections I-V, Optional: sections VI-VIII.] [Optional: Richard Montague (1973). The Proper Treatment of Quantification in Ordinary English.] HW2 assigned tomorrow. Section 1 readings responses on piazza, other sections comment.
2/5	Terry Winnograd: The Good and Bad of AI, The HCI Solution Readings: Winograd (2006). Shifting viewpoints: Artificial intelligence and human-computer interaction. Winograd (1990). Thinking machines: Can there be? Are We? Reading responses this week: Ben's section (others comment).	2/7	Jay McClelland: Parallel Distributed Processing Readings: Rumelhart (1989). The Architecture of the Mind: A Connectionist Approach (pdf) McClelland and Rogers (2003), The Parallel Distributed Processing Approach to Semantic Cognition HW 2 due tomorrow.
2/12	Deep Learning Lecture Slides Readings: [Optional: Deep Belief Networks (Scholarpedia)] [Optional: Extended video tutorial on Deep Belief Networks, Hinton] [Optional: Hopfield (1982), Neural networks and physical systems with emergent collective computational abilities (pdf)] Reading responses this week: Dasha's section (others comment).	2/14	Probabilistic Cognitive Science I Lecture Slides Readings: Tenenbaum, Kemp, Griffiths, and Goodman (2011). How to grow a mind: structure, statistics, and abstraction. Frank and Goodman (to appear). Quantifying pragmatic inference in language games. HW3 assigned tomorrow.
2/19	Probabilistic Cognitive Science II Lecture Slides Readings: Ananthaswamy (2011). I, algorithm. Pearl (1985). Bayesian Networks: a Model of Self-Activated Memory for Evidential Reasoning. Reading responses this week: Jean's section (others comment).	2/21	Probabilistic Cognitive Science III Lecture Slides Readings: Goodman (2013). The Principles and Practice of Probabilistic Programming. Read as much as you want of the Probabilistic Models of Cognition tutorial. HW3 due tomorrow.
2/26	Mike Frank: Langauge Development Lecture Slides Readings: Kuhl (2004). Early langauge acquisition: Cracking the speech code. Reading responses this week: Ben's section (others comment).	2/28	The Nativist vs. Empiricist debate! Lecture Slides Readings: Pinker (2004). Why nature and nurture won't go away. Spelke (1998). Nativism, empiricism, and the origins of knowledge. HW4 assigned tomorrow.
3/5	Reinforcement Learning and the Brain I Lecture Slides Readings: Montague, Hyman, Cohen (2004). Computational roles for dopamine in behavioural control. Rangel, Camerer, Montague (2008). A framework for studying the neurobiology of value-based decision making. Reading responses this week: Dasha's section (others comment).	3/7	Reinforcement Learning and the Brain II
3/12	Inference algorithms in machines and brains Readings: Berkes, Orban, Fiser, Lengyel (2011). Spontaneous Cortical Activity Reveals Hallmarks of an Optimal Internal Model of the Environment. Vul, Goodman, Griffiths, Tenenbaum (2009). One and done: Globally optimal behavior from locally suboptimal decisions. Reading responses this week: Jean's section (others comment).	3/14	Wrap-up Lecture HW 4 due today.