CSCI-100 Introduction to Computing

1
CSCI-100Introduction to Computing

• Artificial Intelligence

2
What is AI?

• Artificial intelligence (AI) is usually defined
  as the science of making computers do things that
  require intelligence when done by humans

3
What is Intelligence?

• The ability to think and act rationally
• The capacity to learn
• Consider the behavior of the digger wasp. When
  the wasp brings food to her nest, she puts it on
  the entrance, goes inside to check for intruders
  and, if the coast is clear, carries in the food.
  If you move the food a few inches while the wasp
  is inside checking, on emerging, the wasp repeats
  the whole procedure (i.e., it carries the food to
  the entrance, goes in to look around, and emerges
  again)

Dumb insect
4
Whats involved in Intelligence?

• Ability to interact with the real world
• to perceive, understand, and act
• speech recognition, understanding
• Image understanding (computer vision)
• Reasoning and planning
• Modeling the external world
• Problem solving, planning, and decision making
• Ability to deal with unexpected problems,
  uncertainties
• Learning and Adaptation

5
Whats involved in Intelligence?

• Research in AI has focused mainly on the
  following components of intelligence
• Learning
• Reasoning
• Problem Solving
• Perception
• Language Understanding

6
Strong AI

• Strong AI aims to build machines whose overall
  intellectual ability is indistinguishable from
  that of a human being
• The ultimate goal of strong AI is nothing less
  than to build a machine on the model of a man, a
  robot that is to have its childhood, to learn a
  language as a child does, to gain its knowledge
  of the world by sensing the world through its own
  organs, and ultimately to contemplate the whole
  domain of human thought Joseph Weizenbaum, MIT
  AI Laboratory

7
Applied AI

• Applied AI aims to produce commercially viable
  smart systems (e.g., a security system that is
  able to recognize the faces of people who are
  permitted to enter a particular building)
• Applied AI has enjoyed considerable success

8
Different Approaches
Against human performance
Against ideal concept of intelligence
(rationality)
Systems that think like humans Systems that think rationally
Systems that act like humans Systems that act rationally
Thinking
Behavior
9
Thinking Humanly Cognitive Science

• Claim A given program thinks like a human
• Must have some way of determining how humans
  think
• Need to get inside the actual workings of human
  minds
• After we have a theory of the mind, can express
  it as a computer program
• If programs I/O and timing matches corresponding
  human behavior, evidence that our theory is
  correct

Systems that think like humans Systems that think rationally
Systems that act like humans Systems that act rationally
10
Thinking Humanly Cognitive Science

• The interdisciplinary field of cognitive science
  brings together computer models from AI and
  experimental techniques from psychology to try to
  construct precise and testable theories of the
  workings of the human mind

11
Thinking Rationally Laws of Thought

• Aristotle
• Attempted to codify right thinking (i.e.,
  correct arguments)
• His syllogisms provided patterns for argument
  structures that always yielded correct
  conclusions given correct premises
• Socrates is a man
• All men are mortal
• ? Socrates is mortal
• By 1965, programs existed that could, in
  principle, solve any solvable problem described
  in logical notation
• The logicist tradition within AI hopes to build
  on such programs to create intelligent systems

Systems that think like humans Systems that think rationally
Systems that act like humans Systems that act rationally
12
Acting Humanly The Turing Test
Systems that think like humans Systems that think rationally
Systems that act like humans Systems that act rationally
ELIZA, computer therapist
13
Acting Humanly The Turing Test

• Proposed by Alan Turing (1950) (the father of AI)
• Based on indistinguishability from undeniably
  intelligent entities (i.e., we)
• Is a computer that passes the test really
  intelligent?
• Programming a computer to pass the test provides
  plenty to work on
• Natural Language Processing
• Knowledge Representation
• Automated Reasoning
• Machine Learning

14
Acting Humanly The Turing Test

• Physical simulation of a person unnecessary for
  intelligence thus no need for physical
  interaction between interrogator and computer
• Total Turing Test
• Interrogator can test the subjects perceptual
  abilities
• Interrogator can pass physical objects through
  the hatch
• Computer would need computer vision, robotics

15
Acting Humanly The Turing Test

• Today, AI researchers devote little effort to
  passing the test
• More important to study underlying principles of
  intelligence
• Turing Test suggested major components of AI
• Natural Language Processing
• Knowledge Representation
• Automated Reasoning
• Machine Learning
• Computer Vision
• Robotics

16
Acting Rationally Rational Agents

• Rational behavior doing the right thing
• The right thing that which is expected to
  maximize goal achievement, given the available
  information
• Doesnt necessarily involve thinking (e.g.,
  blinking reflex) but thinking should be in the
  service of rational action

Systems that think like humans Systems that think rationally
Systems that act like humans Systems that act rationally
17
Acting Rationally Rational Agents

• An agent is an entity that perceives and acts
• Examples of Agents?
• Sensors and Actuators in
• A Human Agent?
• A Robotic Agent?

18
Acting Rationally Rational Agents (Advantages)

• In the Laws of Thought approach to AI, emphasis
  is on correct inferences
• Making correct inferences is sometimes part of
  being a rational agent but not all of
  rationality. Why?
• Sometimes there is no provably correct thing to
  do, yet something must still be done
• There are ways of acting rationally that cannot
  be said to involve inference (e.g., recoiling
  from a hot stove)
• Thus, more general than the Laws of Thought
  approach

19
Acting Rationally Rational Agents (Advantages)

• More suitable for scientific development that
  approaches based on human behavior or human
  thought because standard of rationality is
  clearly defined and completely general

20
AI History

• History of AI is commonly supposed to begin with
  Turings 1950 discussions of machine intelligence
  and to have been defined as a field at the 1956
  Dartmouth Summer Research Project on Artificial
  Intelligence
• But ideas on which AI is based, symbolic AI in
  particular, have a very long history in the
  Western intellectual tradition, dating back to
  ancient Greece

21
Symbolic AI

• Approach to AI that has dominated the field
  throughout most of its history
• Based on the Physical Symbol System Hypothesis,
  enunciated by Newell and Simon (1976)
• A physical symbol system has the necessary and
  sufficient means for general intelligent action
• Knowledge represented in brain by language-like
  structures or formulas
• Thinking is a computational process that
  rearranges such structures according to formal
  rules

22
The Roots of Formal Logic

• In ancient Greece, pebbles were used for
  calculation in a similar way to beads on an
  abacus
• Latin word for pebble is calculus
• In logic and math, we use the word calculus for
  any system of notation in which we can accomplish
  some purpose by manipulation of tokens according
  to formal, mechanical rules (e.g., propositional,
  predicate calculus)
• To the extent that such rules are purely
  mechanical, they can, in principle, be carried
  out by a machine
• If a process can be reduced to a calculus, it can
  be calculated by a machine

23
Neuroscience

• Neuroscience (1861 present)
• How do brains process information?
• Brain consists of brain nerve cells or neurons
• A neuron makes connections with other neurons at
  junctions called synapses
• Signals are propagated from neuron to neuron
• The signals enable long-term changes in
  connectivity of neurons
• Thought to form the basis for learning in the
  brain
• A collection of simple cells can lead to thought,
  action, and consciousness or, in other words,
  that brains cause minds (Searle, 1992)
• Alternative is mysticism there is a mystical
  realm in which minds operate that is beyond
  physical science

24
Connectionism

• Has only recently become a serious contender to
  symbolic AI
• The level of the symbol is too high to lead to a
  good model of the mind
• Have to go lower instead of designing programs
  that perform computations on such symbols, design
  programs that perform computations at a lower
  level (the neuron)
• When viewed at the semantic levels such systems
  often do not appear to be engaged in
  rule-following behavior (rules lie at a deeper
  level)