Cog Sci 4 - The Computational Theory of Mind

Representations

Symbols, pictures, and other things that stand for an object, an abstract concept, or other things

Who talks about how neuroscience contributes to the study of the mind as an information processer?

David Marr, the first computational neuroscientist

How can neuroscience contribute to the study of the mind as an information processer?

Analyze computations at different levels of analysis

What are the levels of analysis

• Computational Level

• Algorithmic Level

• Implementational Level

Computational Level

WHAT and WHY

What is the goal of the computation?

Why does it do the computation?

Algorithmic Level

HOW

How is the computation carried out?

How are the input and output represented?

What specific steps are taken in the process from input to output?

Implementational Level

WHERE

How is the computation realized in a physical system?

What physical structures and processes are involved?

Higher Level of Abstraction

Cognitive processes are computations

Computational and Algorithmic Level

Lower Level of Abstraction

Cognitive processes are implemented in neural structures

Implementational Level

Face Perception at a Computational Level

What is the goal of face perception? What is the need of face perception?

Input —→ Output

Light —→ Recognizing Faces

Face Perception at an Algorithmic Level

How is the computation carried out?

What steps does the mind take to recognize visual input?

What kind of representations are involved in recognizing faces?

Face Perception at Implementation Level

What is the physical systems that executes the steps of the algorithm?

Weak AI

Strong AI

Physical Form for Strong AI

Multiple Realizability Argument

Functionalism

Sensory Stimuli

Other Mental States

Behavior

Formal Systems

Symbols

Grammar

Rules of Inference

Syntax vs Semantics

The Physical Symbol System Hypothesis

Qualia

Inverted Qualia

The Inverted Qualia Problem