1. Artificial Intelligence Mr. Sciame Section 2
The Foundations of AI
Artificial Intelligence
Mr. Sciame
Section 2

2. First Foundation

3. Philosophy (428 BC – Present)
Questions for AI
Can formal rules be used to draw valid conclusions?
How does the mental mind arise from a physical brain?
Where does knowledge come from?
How does knowledge lead to action?

4. Applying Rational Thought to Machines
Aristotle – Formulated Logic
Da Vinci – Designed the first calculator
Wilhelm Schickard – 1st Calculating machine (1623)
Blaise Pascal – The Pascal Adder (1642) – The more famous calculating machine; much like an odometer on a car.

5. Pascal and His Adder

6. The Mind as a Physical System
René Descartes ( ) was first to clearly discuss the distinction between mind and matter.
A physical mind leaves no room for free will.
If the mind was governed by physical laws, it has the free will of a rock “deciding” to fall to Earth.

7. Dualism Descartes proposed dualism
There is a part of the human mind (soul or spirit) outside of nature.
This part was exempt from physical laws.
He felt animals did not possess this dual nature and could be treated as machines.

8. Materialism Alternative to dualism
The brain’s operation according to the laws of physics constitutes the mind.
Free will is the perception of available choices in the choice process.

9. Establishing the Source of Knowledge
Empiricism
Nothing is in the understanding, which is not first in the senses. – John Locke
Induction
General rules are acquired by exposure to repeated associations between their elements.
Logical Positivism
Knowledge can be characterized by logical theories connected to observational sentences that correspond to sensory inputs

10. Connection of Knowledge to Action
A vital question for AI, since intelligence requires actions as well as reasoning.
There must be an understanding of how actions are justifiable (or rational).

11. Aristotle
We deliberate not about ends, but about means.

12. Second Foundation

13. Mathematics (800 AD – Present)
Questions for AI
What are the formal rules to draw valid conclusions?
What can be compared?
How do we reason with uncertain information?
Three contributions
Logic
Computation
Probability

14. The Formal Rules George Boole (1847) Gottlob Frege (1848-1925)
Boolean Logic
Gottlob Frege ( )
Extended Boolean logic to include objects and relations, used today as a basic knowledge representation system.
Alfred Tarski ( )
His theory showed how to relate objects in a logic to objects in the real world.

15. The Limits of Logic and Computation
Algorithms
Step by step methods for problem solving.
The incompleteness theorem
Some Functions cannot be represented by algorithms.
The Turing Machine (1936 – Alan Turing)
You could create a machine capable of computing a computable function
No machine can tell in general whether a given program will return an answer, or run forever.

16. Probability
The possible outcomes of gambling events

17. THIRD Foundation

18. Economics (1776 to Present)
Questions for AI:
How should we make decisions as to maximize payoff?
How should we do this when others may not go along?
How should we do this when the payoff may be far into the future?

19. Historical
Adam Smith (1776) – An Inquiry into the Causes of the Wealth of Nations.
First time Economics is treated as a science.
The study of making choices that lead to preferred outcomes.
Theory updated by John von Neumann (1944) The Theory of Games and Economic Behavior.

20. Decision Theory The Decision Theory: Combines Probability with Utility
Provides a framework for decisions
This works for large economies (it doesn’t matter what the other guy does); smaller ones treat this as a game (the actions of one affect others)

21. Payoff for the Future Herbert Simon (1978) Won the Nobel Prize
Showed that making decisions that were “good enough,” rather than looking for an optimal decision, gave a better description of human behavior.

22. FOURTH Foundation

23. Neuroscience (1861 to Present)
Questions for AI:
How do brains process information?

24. Definition
Neuroscience is the study of the nervous system, and in particular, the brain.

25. The Neuron
Parts include:
Cell Body
Dendrites
Axon

26. Comparason Computer Human Brain Computational Units 1 CPU, 108 gates
1011 neurons
Storage Units
1010 bits RAM
1011 bits disk
1014 synapses
Cycle Time
10-9 seconds
10-3 seconds
Bandwidth
1010 bits/second
1014 bits/second
Memory Updates/Second
109
1014

27. FIFTH Foundation

28. Psychology (1879 to Present)
Questions for AI:
How do humans and animals think and act?

29. Studies
Behavioralism
Cognitive Psychology
Cognitive Science

30. Behaviorism The study of animal behavior
Relationship of stimuli to responses

31. Cognitive Psychology
The view of the brain as an information processing device.
Three steps of a knowledge based agent:
The stimulus must be turned into an internal representation
The representation is changed by cognitive processes into new internal representations
These are translated back into actions.

32. Cognitive Science
Addresses the psychology of memory, language, and logical thinking
“A cognitive theory should be like a computer program” (Anderson, 1980)
AI Examples:
Newell and Simon’s The Logical Thinking Machine
Noah Chomsky and language

33. SIXTH Foundation

34. Computer Engineering (1940 to Present)
Questions for AI:
How can we build an efficient computer?
We discussed this in our first notes.

35. SEVENTH Foundation

36. Control Theory and Cybernetics (1948 to Present)
Questions for AI:
How can artifacts operate under their own control?

37. Inventions of Control Devices
250 BC – Water Clock
1600’s – Thermostat (Drebbel)
1800’s – Steam Engine (James Watt)

38. Theories Control Theory: Objective Function
A regulatory mechanism trying to minimize “error” (the difference between the current state and the goal state)
Objective Function
Designing systems that behave optimally.

39. EIGHTH Foundation

40. Linguistics (1957 to Present)
Questions for AI:
How does language relate to thought?

41. Books on the Subject Verbal Behavior – B.F. Skinner
Syntactic Structures – Noah Chomsky
Skinner:
Behaviorialist Approach
Chomsky:
Creativity in language
Children’s sentences.

42. Natural Language Processing
Understanding Language:
Not just sentence structure.
Also subject matter and context