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CTM 2. Exam 2. Exam 1. Exam 2. Letter Grades. Statistics. Mean: 60 Median: 56 Modes: 51, 76. THE COMPUTATIONAL THEORY OF MIND CONTINUED. The Computational Theory of Mind.
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Statistics Mean: 60 Median: 56 Modes: 51, 76
The Computational Theory of Mind The computational theory of mind says that the brain is a universal computer and that the mind is the program that it runs. It is a version of functionalism, since what makes something a computer is not what it’s made out of (transistors, dominoes, Legos, brain cells) but instead it’s the relations of its states.
Mental States are Multiply Realizable There’s already plenty of reason to believe in functionalism, and CTM is just a type of functionalism that is more detailed and explains more things (e.g. rationality).
Mental Processes are Rational processes are reason-respecting. Many of your mental states cause other mental states, and do so in a way that if the causing states represent something that is true, then the caused state represents something that is also true.
Logical Relations From: • If Joe fails the final exam, he will fail the course. • If Joe fails the course, he will not graduate. It follows logically that: 3. If Joe fails the final exam, he will not graduate.
Logical Relations If you believe: • If Joe fails the final exam, he will fail the course. • If Joe fails the course, he will not graduate. These beliefs can cause you to also believe: 3. If Joe fails the final exam, he will not graduate.
Mental Processes are Rational Computers are the only things (besides minds) that we have so far discovered that are reason-respecting in this way. This gives us some reason to think that maybe minds are in fact computers.
No Computation without Representation As we’ve seen, to be a computer requires that one be able to represent and manipulate representations of the inputs and outputs to functions. This means that IF the brain is a computer, and the mind is its software, THEN the mind has representational states.
The Language of Thought If the mind has representational states, then there is some format the representations are in. One idea is that the format is a language that is a lot like a computer language for an electronic computer or a natural, spoken human language: the language of thought (sometimes: “Mentalese”).
The Language of Thought The idea would be that when you think “dogs hate cats,” there are discrete ‘words’ of the language of thought, DOGS, HATE, CATS. These are your ideas. The thought is a ‘sentence’ that is made out of those ideas: DOGS HATE CATS
Systematicity You can use those same ideas in different combinations: CATS HATE DOGS The LOT hypothesis thus predicts mental systematicity: that people who can think that cats hate dogs can think that dogs hate cats.
Systematicity Thought is systematic := For any thought T containing a concept (idea) C, and any concept C* of the same category as C: anyone who can think T(C) can think T(C*). Categories: concepts that represent individuals (“names”), concepts that represent properties (“adjectives,” “intransitive verbs”) concepts that represent logical relations (“connectives”), etc.
Systematicity Sometimes Fodor just says: Thought is systematic := anyone who can think aRb can think bRa.
The Argument from Systematicity • If the LOT hypothesis is true, then thought should be systematic. • It seems like thought is systematic. • The best explanation of the systematicity of thought is that LOT is true.
Compositionality A representational system is compositional := what complex representations represent is determined completely by what their basic symbols represent.
Basic Symbol A basic symbol is just a symbol that has no meaningful parts. Classic example ‘cattle’ contains the part ‘cat,’ but that part of it has no meaning in the expression ‘cattle.’
FROM POLICE RUNS MICHAEL
Novel Utterance “Yesterday, on my way to the plastic cow hat factory, I witnessed on two separate occasions police selling cupcakes out of empty space shuttles that had been painted in red and blue stripes.”
Compositionality and Natural Language Many linguists think that the only way we can understand an infinite number of different sentences with different meanings is if those sentences are compositional. This way we can learn a finite number of meanings (for individual words) and use those to calculate the meanings for all the more complicated expressions (like sentences).
Productivity A representational system is productive := that system contains an infinite number of representations with an infinite number of distinct meanings.
The Argument from Productivity • Thought appears to be productive. We can think a potential infinitude of different things. There will be no point at which humans have “thought all the thoughts.” • If thought occurs in a language, we can use a compositional meaning theory to assign meanings to each thought on the basis of the meanings of their simple parts (concepts).
The Argument from Productivity Therefore, the best explanation for the productivity of thought is that thought involves a language-like representational medium, and has a compositional semantics. LOT is true.
The Turing Test Turing didn’t just discover the theory of computation, he also proposed a test for deciding whether a machine could think.
Chatterbots ELIZA, 1966 http://nlp-addiction.com/eliza/ (Joseph Weizenbaum, creator)
Simon & Newell The heuristic search hypothesis says: “The solutions to problems are represented as symbol structures. A physical symbol system exercises its intelligence in problem solving by search--that is, by generating and progressively modifying symbol structures until it produces a solution structure.” (Computer Science as Empirical Enquiry, 1976)
