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PHIL 133
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Making Minds

A Constructive Introduction to the Computational Theory of Mind
​Philosophy 133 • Professor Gabriel Greenberg
TTh 4-5:50 • Zoom links on CCLE
Course description:  How does the human mind arise from a physical brain?   How could perception, reasoning, and memory all emerge from unthinking matter?  According to the Computational Theory of Mind, the brain is a biological computer, and cognition is its function.   We'll examine this idea from a philosophical and logical perspective.  Starting with the simplest mechanical parts, we will gradually build up layers of complexity, computational power, and abstraction. By the end of the course, we'll be able to design organisms exhibit fundamental forms of of cognition.  Along the way we'll touch upon the nature of representation, language, memory, algorithms, levels of abstraction, and the interaction between the mind and the environment.   Requirements include: • daily readings; • 6 problem sets; • optional final project; • lecture attendance; • no final exam. Warning: this course is time-intensive!

Announcements
  • HW 6 due date CHANGE
    ​Now Due Friday, March 12, 11:59 pm.
  • HW7 due date
    Thursday, March 18, 11:59 pm.
Sections + Office hours 
  • Zhang sections: F 1-2 / 2-3
  • Greenberg office hours:
    ​Philosophy: T 6-7
    Homework: Th 6-7 
  • Zhang office hours: M 12-2
  • All zoom links on CCLE.
Course book
  • Making Minds (MM) current update
  • [old] Making Minds (MM) complete book
 ​Homework assignments
  • HW 1: Basics
  • HW2: Computing with CCs
  • HW3: Computing with SCs 
  • HW4: Computing with FSMs
  • HW5: Computing with TMs
  • HW6: Navigating with Turbots
  • HW7: Final project

Syllabus

(T) = Technical text.
(C) = Conceptual text.
* = Classic text.

Unit 1: Computation

1.1 The Cognition-Body Problem
​​T 1/5
​MM 1-2
Read:
  • Syllabus (this page) and Course Policies.

1.2 Logic Gates & Combinatorial Circuits
Th 1/7
​MM 3
Read:
  • (T)(C) Hillis (1999) The Pattern on the Stone, "Preface: Magic in the Stone," Ch. 1: "Nuts and Bolts," Ch. 2: "Universal Building Blocks" (through p. 30)
  • (C) Lau et al (2020) "Neurons" and "Neuronal Circuits" [youtube]
Of interest:
  • (C) Edelman (2008) Computing the Brain, Ch. 3: "Computing Brains" pp. 37-44, 50-58​
Reading Guide
The Hillis reading will be essential to understanding the technical concepts we will discuss in class and for HW1: logic gates, logic circuits, and their relationship to computation.

The Edelman reading won't be the main focus of discussion, but it is part of a bigger picture that we will build up each week, about the analogies between the logic-based computers and the neural circuitry of the brain.

2.1 Functions & Representations
​T 1/12
MM 4-5
Read:
  • (T) Petzold (200) Code, Ch. 7: "Our Ten Digits" and Ch. 8: "Alternatives to Ten"  (2000) Petzol
  • (T) Redwoods Department of Mathematics (2007) "Introduction to Functions"
  • (C) Edelman (2008) Computing the Brain, Ch. 2: "Computing Minds" pp. 13-25
Useful:
  • (C) Gallistel and King (2009) Memory and the Computational Brain, Ch. 3: "Functions"
Reading Guide
The reading by Petzold introduces the concept of a representational system, in particular, the base-2 binary counting system.   The reading by Redwoods provides important background on the mathematical concept of a function.   Both will be critical to class discussion and HW1.

The Edelman reading is an insightful introduction to the concept of representation, a central idea within CTM.   These concepts  will become more important in the next few weeks as we discuss CTM in greater detail, and will be relevant for the philosophical questions in HW2 and the final project.

HW1.  Basics: Circuits, Functions, and Representations
Due Th 1/14, 4PM PST (before class)

2.2 Computation with Combinatorial Circuits (CCs)
​Th 1/14
Handout: MM 6
Read:
  • (C) Crane (2003) The Mechanical Mind, Ch. 3: "Computers and Thought" pp. 83-114 only (skim 92-99)
  • (T*) Cummins (1991) Meaning and Mental Representations, Ch. 8: "Interpretational Semantics" (excerpt)
Reading Guide
So far we've studied circuits, functions, and representational systems.  We now combine all three elements to define computation.

Start by focusing on the the reading by Crane​, which is an accessible description to the relationship between functions, algorithms, and computation.  What is the difference between instantiating and computing a function?  What is an automatic algorithm?

The Cummins reading is a classic statement on the concept of computation, with special attention to the role of representation.  This text is difficult and rather abstract, but you will achieve a deeper understanding of the course material if you can tame it.

3.1 The Story of Binary +1 (CC)
​T 1/19
Handout: MM X
Read:
  • (T) Petzold (2000) Code, Ch. 12: "A Binary Adding Machine"
  • ​(C) Dixon (2017) "How Aristotle created the computer"

3.2 Natural and Artificial Computers
​Th 1/21
Handout: ​MM X
Read:
  • (C*) Craik (1943) The Nature of Explanation, Ch. 5: "Hypothesis on the Nature of Thought"
  • (C) Pinker, (1997) How the Mind Works, Ch. 2: "Thinking Machines" (excerpt)

Of interest:
  • (C) Lande (2019) "Do you compute?"  (written by a former student from this class!)
Reading Guide
The point of these readings is to get an intuitive idea of the Computational Theory of Mind, aka CTM or Computationalism.

The chapter by Craik is one of the first vivid statements of CTM.   This is a difficult article, but it lays out a deeply insightful vision of how organisms might use neural symbols to negotiate the world, and why this would be such a winning evolutionary strategy.   Read for the big picture.  As you read, ask yourself, what exactly is Craik's "hypothesis" on the nature of thought?

The Pinker reading provides an easier to read and more familiar introduction to CTM.   Pinker frames CTM as a claim about natural computation, i.e. the claim that the brain just is a natural computer.   What does pinker mean by "natural" computation?  What is the difference between natural and artificial computation?

HW2.  Computing with CCs
Due T 1/26, 2PM PST (before class)

4.1 Computational Theory of Mind
T 1/26
​Handout: ​MM X
Read:
  • (C) McGlaughlin (2004) "Computationalism, Connectionism, and the Philosophy of Mind" — pages 135-141 only.
  • ​(Haugeland, Semantic Engines)
​Background:
  • (C) Ravenscroft (2005) Philosophy of Mind, Ch. 6: "The Computational Theory of Mind"
  • (C) Johnson-Laird (1988) "How Should the Mind Be Studied?".  [Trying to find a PDF]
Reading Guide
Note: CTM = Computationalism

The purpose of the McGlaughlin reading is to provide a clear and concise statement of CTM.  After reading the article see if you can define CTM for yourself.   The article also does a nice job of showing how CTM connects to what we have done (logic gates and logic circuits), whats coming up next (levels of computational analysis), and what lies further ahead (intelligent thought).

Unit 2: Levels

4.2 Memory and Sequential Circuits (SCs)
Th 1/28
MM X
​Read:
  • (C) Braitenberg (1986) Vehicles: Experiments in Synthetic Psychology, Ch. 5: "Vehicles"
  • (T) Know the Code (2021) "Basics of Memory Circuits"   [video]
Reading Guide
The Braitenberg chapter considers how logic and memory might be added to simple machines--- not quite the same machines we've been dealing with, but not so different either.  What is the central intuition behind building a machine with physical memory?  See if you can imagine how to extend Braitenberg's suggestion into a concrete implementation of memory in a logic circuit.

The Know the Code video provides a personable and practical introduction to the workings of computer memory.  You won't be responsible for reconstructing the internal circuitry of a "flip-flop"-- the basis of digital memory-- but do your best to follow along throughout.  The general concepts of memory and time will be important in Unit 2.

5.1 Computing in Time
​​
T 2/2
MM 13
​Read:
  • (T) Neso Academy (2015) "Comparison between Combinational and Sequential Circuits"
  • (T) Neso Academy (2015) "Introduction to Sequential Circuits"
Reading Guide
Text.

5.2 Computational Power
Th 2/4
MM X
​Read: 
  • ​(C*) Chomsky (1957) Syntactic Structures, pgs 11-25
Reading Guide
Text.

HW3.  Computing with SCs
Due T 2/9, 2PM PST (before class)

6.1 State Abstraction
T 2/9
MM X
​Read:
  • (T) Patterson and Hennessy (2018) "Finite State Machines"
  • (C*) Putnam (1960) "Minds and Machines" (excerpt)
​Of Interest:
  • (C*) Putnam (1967) "The Nature of Mental States"
  • (C*) Putnam (1975) "Philosophy and Our Mental Life"
Reading Guide
Text.

6.2 Finite State Machines (FSMs)
& the Algorithm Concept

Th 2/11
MM X
Read: 
  • (C) Hillis (1999) "The Pattern on the Stone" --- pages 30-38 
  • (T) Gkasdrogkas (2019) "An Example-based Introduction to Finite State Machines" (Skip NFAs)
  • (C) Review the discussion of algorithms from the Crane reading for Week 3.1.
Reading Guide
Text.

7.1 Levels of Abstraction
T 2/16
MM X
Read:
  • (C*) Putnam (1975) "Philosophy and Our Mental Life" (excerpt)
  • ​(C*) Marr (1982) "Understanding Complex Information-Processing Systems"
Reading Guide
Text.

​HW4.  Computing with FSMs
Due 2/18

Unit 3: Cognition

7.2 Turing Machines (TMs)
Th 2/18
MM X
​Read: 
  • (T*) Turing (1936) "On Computable Numbers, with an Application to the Entscheidungsproblem" (excerpt)
  • ​(T) Boolos, Burges, and Jeffries (2007) Computability and Logic, Ch. 3 "Turing Computability"
Of interest:
  • The Imitation Game (2014) - a Hollywood biopic about Alan Turing
  • LEGO Turing Machine [youtube]
  • Wood Turing Machine [youtbue]
Reading Guide
Text.

8.1 Recursive Algorithms
T 2/23
MM X
Read: 
  • Hillis (1999) "Programming"
Of interest:
  • Miller, Galanter, Pribram (1960), "The Unit of Analysis" from Plans and the Structure of Behavior

Reading Guide
Text.

8.2 Computing with TMs
Th 2/25
MM X
​Read:  Gallistel and King, ​Preface
Reading Guide
Text.

​HW5.  Computing with TMs
Due 3/2

9.1 Navigation + Physical Cognition
T 3/2
MM X
Read:
 
  • Goldman (2012) "Desert Ants are Better at Trigonometry than Most High-School Students"  
  • Gallistel (1998) "Insect Navigation: Brains as Symbol-Processing Organs"
Reading Guide
Text.

9.2 Machines & Programs
​
Th 3/4
MM X
​Read: see announcements at top of page.
Optional:
  • (C*) Pylyshyn (1980) “Computation and Cognition: issues in the foundations of cognitive science" -- Sections 1-6
Reading Guide
Text.

10.1 The Universal Machine
T 3/9
MM X
Read:
  • ​TBA
Of interest:
  • (C*) Pylyshyn (1980) “Computation and Cognition: issues in the foundations of cognitive science" -- Sections 7-11
  • (C) Lewis-Krauss (2016) "The Great AI Awakening" [NYTimes article]
  • (C) Kohs (2020) "AlphaGo" [Documentary]
Reading Guide
Text.

10.2 Computation & Consciousness
Th 3/11
Read:
  • (C) Baars (1988) "The Global Workspace Theory of Consciousness"
Recommended:
  • (C) Lau and Rosenthal (2011) "Empirical support for higher-order theories of conscious awareness"
  • McDermott (2007) "Artificial Intelligence and Consciousness"
Of interest:
  • (C)(T) Aaronson (2013) "Why Philosophers Should Care About Complexity Theory"
Reading Guide
Text.

​HW6.  Navigation with Turbots
Due 3/12, 11:59 PM

​HW7.  Final Project (optional)
Due Thursday March 18, 11:59 PM.
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