Cognitive Science - Introduction

Front 1

What is cognitive science, in terms of what cognition is?

Back 1

- Cognition is information processing, and operates on representations (symbols that have meaning)

- CS takes a scientific approach: we develop theories to explain phenomena

- study of information and representation processing can be divorced from biology and physiology, where computers can make talking about representations more precise

- CRUM

Front 2

CRUM: Computational-Representation Understanding of Mind

Back 2

- rather than just looking at an environment to explain behavior, we should look at representations
- to learn about representations, we look towards linguistics, psychology, neuroscience

Front 3

What are the criteria for a theory of thought?

Back 3

we need a mathematical language that can formally express our thoughts and link them to the world

- similarly to how calculus relates to motion in the world, and geometry to location in the world

Front 4

what do mathematical theories of thought do?

Back 4

they should "represent the relationships between our thoughts"

they should be an algebra that vields valid inferences

Front 5

what are syllogisms and what is Aristotle's relationship to them?

Back 5

Aristotle tried to compile together all syllogisms,

these are logical arguments where one proposition is inferred from two others

Front 6

What did Leibniz try to do?

Back 6

he tried to create an algebra that yields valid inferences, a mathematical language that could formalize our thoughts

Front 7

What is Boole's logic what are its limits?

Back 7

x=1 is true, x=0 is false. it locks us into very simple conclusions and doesn't have quantifiers (existential or universal)

Front 8

modus ponens truth table

Back 8

X Y X => Y
___________

T T T

T F F

F T T

F F T

Front 9

modus ponens proof

Back 9

X => Y

X
___

Y

Front 10

modus tollens proof

Back 10

X => Y

not Y

__

not X

Front 11

how is frege's modern logic different than logics before it?

Back 11

it uses proposition logic that takes the form proposition(object)

hairy(Rex) = "Rex is hairy"
IsAGSI(Paul) = "Paul is a GSI"

Front 12

Entscheidungsproblem and its conclusion

Back 12

can we make a machine that can take premises in first-order logic and indicate whether conclusions are true or false?

- most likely impossible, since it would have to know every fact in the world. this would involve some knowledge of semantics

Front 13

define a Turing machine

Back 13

a computational machine that runs on a set of rules (its program), has a head that marks numbers on a long tape. the head can move along the tape as it likes, as long as it is written into the program

Front 14

halting problem

Back 14

once a Turing machine starts to compute, there's no way of knowing whether it will terminate in an answer

Front 15

difference between hardware and software

Back 15

hardware is the physical structure while software is the the program that this machine runs on

Front 16

what are symbols?

Back 16

symbols are representations that have meaning. they represent something to us. (e.g. letters in a certain language represent sounds)

Front 17

symbol grounding problem

Back 17

our minds, and especially robots' “minds”, may not know when the facts that correspond to our symbols are true (e.g. What is red?)

Front 18

Descartes' assumptions of the mind and the problems and wonders these entail

Back 18

Descartes believed that the mind and body are separate since we can deny belief of our body but not our mind (we affirm our mind by thinking).

Problems this poses: how do the senses communicate with the mind, and how does the mind cause the body to act?

Front 19

our mind and changing symbols

Back 19

symbols can change as long as they have the same relationships

the world can change as long as the symbols have the same truth values (but this would lead us into a Matrix-like situation)

Front 20

Descartes' solution to the mind-body problem

Back 20

humans have a pineal gland where something can be sent across, from the brain to the body. conceptually he was right, but none of his details were.

Front 21

universal Turing machine

Back 21

a Turing machine that can simulate as many other Turing machines as it wants, becoming something that seems more like a brain

Front 22

What does cogsci allow us to do with minds, in terms of our level of analysis?

Back 22

we're able to study any type of mind at a level of abstraction above its physical form.

- one level of analysis: physical. hard to understand how our brain might work on this level
- another level: mathematical. study our thought by formalizing it into a mathematical language

Front 23

Plato vs. Locke, nativism vs. empiricism

Back 23

Plato: we remember facts from before our birth. What we see are shadows of an ideal world that are close enough for us to see it as this world

Locke: blank slate. we learn new facts about the world through experiences and perception

Front 24

induction vs. deduction

Back 24

induction: inferring truths from our own experience (so our conclusions could be wrong)

deduction: forming new truths based on other truths

Front 25

complex vs. simple ideas

Back 25

complex ideas are formed from simple ones. a unicorn doesn't exist, yet we can still imagine it. it's simply a horse with a rod on its head.

Front 26

why might we worry about a science of the mind (Wundt's approach to psychology)

Back 26

too introspective, relies on personal subjectivity for answers and experiments

Front 27

Ebbinghaus' approach to psychology (less subjective)

Back 27

tested his memorization every few days, collected data and made conclusions

Front 28

definition of behaviorism and the assumption it makes

Back 28

the environment explains behavior.

assumption: there's no substantial difference between humans and animals, so we can study animals if we want answers

Front 29

classical vs. operant conditioning

Back 29

classical: associating a certain cue with another cue, eliciting a response

operant: using consequence to change behavior
- punishment and reinforcement

Front 30

radical behaviorism

Back 30

disregards mental states and representations, and mental processes. we can understand behavior solely from the environment.

Front 31

Saussure and arbitrariness of signs

Back 31

no inherent direct connection between language symbols and meaning, the signifier (sound/written form) and signified (corresponding concept)

Front 32

synchronic and diachronic linguistics

Back 32

synchronic: the study of a language at this point in time

diachronic: the study of the evolution and history of a language

Front 33

langue and parole

Back 33

langue: abstract rules of a language

parole: how these rules are used in speech

(rules of chess : chess strategy)

Front 34

phonology, morphology, syntax semantics

Back 34

phonology: sounds of a language, combinations of sounds

morphology: how words turn into other words (tense, suffixes, prefixes), a morpheme is the smallest unit of meaning

syntax: how words are combined to form sentences (arrangement, order)

semantics: meaning

Front 35

how behaviorism applies to language

Back 35

language is verbal behavior

problem: language is much too complicated. we can't predict language from environment and this doesn't explain how humans can understand novel sentences

Front 36

mathematical structure of language (Shannon)

Back 36

language is just associations between words and letters. we can use Markov models to predict the next word or letter based on the last one.

problem: phrases in sentences can have arbitrarily long dependencies on other phrases in the sentences

Front 37

Logic Theorist (Simon and Newell)

Back 37

- solved mathematical proofs using human heuristics (problem-solving strategies) when necessary
- used means-ends analysis: took whichever step made it closer to the end
-

Front 38

new ideas from Cognitive Revolution (Newell, Chomsky, Miller)

Back 38

- we can make computer programs that resemble human thought, and we can base these programs on human thought
- we can explore the rules that characterize language and thought through behavior
- we can make inferences about the constraints on mental representations from behavior

Front 39

how did Chomsky counter the validity of Markov models?

Back 39

colorless green ideas sleep furiously. this has never been seen before, and neither word has associations with the one before it, yet it is still grammatically correct.

Front 40

Miller's "Magical Number 7"

Back 40

we can remember up to seven chunks in our short-term memory.

this is an example of looking at behavior to make inferences about human thought. this doesn't explain thought however.

- how can we measure capacity of the mind?
- can it be used as a system of information processing?

Front 41

how can we study representations? (trick question...)

Back 41

this is what cognitive science is! we use psychology, linguistics, neuroscience, etc.

the mapping from environment to behavior is complicated--representations simplify this mapping

Front 42

factors contributing to the defeat of behaviorism / Chomsky's argument

Back 42

- Cognitive Rev presented ideas about using representations to study the mind. there's a complex process our minds go through between the environment and our behavior, and through representations, we can formalize it.

Chomsky: definitions are very hazy. "environment" refers to a ton of stimuli, so how can we predict behavior from the environment if we don't know what stimulus someone is responding to?

- learning is usually not done through operant conditioning reinforcement, but rather, observation

-"We cannot predict verbal behavior in terms of the stimuli in the speaker's environment, since
we do not know what the current stimuli are until he responds"

Front 43

differences between Boole, propositional, and first-order logic

Back 43

Boole is based on true/false, propositional can link an abject and a quality, and first-order can generalize about many objects and their qualities

Front 44

first-order logic: which connective with which quantifier?

Back 44

universal quantifier: =>

existential: ^

Front 45

logic tips

Back 45

- with each quantifier, we must define x and y in the sentence. Man(x) ^ Woman(y)