Intro to Cog Sci Quiz 1

Behaviorism

Study of behavior as a response to stimuli, ignoring internal mental states.

Introspection

• Behaviorists reject it because it is subjective and unobservable. Only observable behavior counts.

  • the examination or observation of one's own mental and emotional processes.

Stimulus-Response (S-R)

Behavior is triggered by stimuli in the environment.

Learning

Forming associations between stimuli and responses

Positive reinforcement

Adding a stimulus to increase a behavior (e.g., giving a treat).

Negative reinforcement:

 Removing a stimulus to increase a behavior (e.g., stopping an annoying sound when the right action occurs).

Skinner Box

Experimental device to study learning in animals, focusing on how reinforcement shapes behavior.

Motivation

Behaviorism couldn’t explain complex behaviors like language or problem-solving.

Tolman (1948): Cognitive Map Experiment

• Rats navigate mazes using internal “maps,” not just learned S-R connections.

• Shows animals can form mental representations, not just conditioned behaviors.

Counterexamples with Language

Humans produce novel sentences, not just memorized responses → suggests internal cognitive rules.

Capacities vs Effects

• Internal ability (e.g., knowing grammar).

• Observable behavior (e.g., speaking a sentence).

• Important distinction: Behavior alone doesn’t fully reveal mental capacities.

Functionalism

Mental states are defined by what they do, not by what they’re made of.

Comparison with Law-Based Explanation

Functionalism explains “what function a mental process serves” vs. behaviorism’s “law-like S-R patterns.”

Properties of Functional Capacities

• Can be multiply realized (same function, different physical form—e.g., human brain vs. AI).

• Individuated by role in a system rather than physical constitution.

Relation to Brain

Brain implements functional capacities but isn’t identical to them.

Computationalism

Mind processes information like a computer—manipulates symbols using formal rules.

Symbols & Formal Rules:

• symbols = representations

• rules = operations on symbols.

Color Perception Example

• Problem: How do we perceive colors consistently?

• Solution: Mind computes based on input signals from retina → assumptions about environment and brain processing.

Why the Mind Compute

• To transform sensory input into behaviorally relevant outputs.

• Goal: Efficient, flexible behavior and reasoning.

Computation

• Turing Machines: Abstract model of computation (input → operations → output).

• Church-Turing Thesis: Anything computable can be computed by a Turing machine.

• Equivalence Argument: Different formal models of computation are equivalent in what they can compute.

Turing Test

• Purpose: Test whether a machine can exhibit human-like intelligence.

• How it Works: Machine convinces a human interlocutor that it is human.

• Problems:

  • Only tests output behavior, not internal understanding.

  • Machines could “cheat” by simulating conversation.

• Alternative Approaches: Test understanding or problem-solving, not just imitation.

Chinese Room Argument

• Thought Experiment: Person follows rules to manipulate Chinese symbols without understanding Chinese.

• Point: Syntax (symbol manipulation) ≠ semantics (meaning).

• Replies/Responses:

  • Systems reply: Maybe the system as a whole understands.

  • Robot reply: Embodiment/environment interaction could create understanding.

Turing Machine Symbols

Arbitrary marks manipulated by formal rules.

Mental Representations

Symbols have external meaning and refer to things in the world.

Representing System vs Represented System

• Representing system: The mind or machine doing the computation.

• Represented system: The thing being represented (e.g., a chair).

Externalism

Mental content depends partly on the environment, not just internal states.