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Introduction - Artificial Intelligence - Lecture Slides, Slides of Artificial Intelligence

Some concept of Artificial Intelligence are Agents and Problem Solving, Autonomy, Programs, Classical and Modern Planning, First-Order Logic, Resolution Theorem Proving, Search Strategies, Structure Learning. Main points of this lecture are: Introduction, Artificial Intelligence, Intelligence, Something Difficult, Dispenser, Intelligence, Achieved By a Machine, Disregard, Prosthetics, Symbiosis

Typology: Slides

2012/2013

Uploaded on 04/29/2013

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Download Introduction - Artificial Intelligence - Lecture Slides and more Slides Artificial Intelligence in PDF only on Docsity!

Artificial Intelligence

Intelligence is in the eye of the beholder

  • We perceive intelligent behaviors (or at least that’s what

we think)

  • But what is intelligent behavior?
    • It deals with doing things that only humans do
    • It deals with something difficult
  • Yet once it is achieved by a machine, we tend to disregard it

and set a new goal for intelligence.

  • For example, an ATM dispenser

Intelligence: our current perspective

  • Doing things that are difficult
  • Mostly we deal with Learning and Adaptation
  • We have let other areas of research to deal with AI
    • Robotics
    • Pattern Recognition
    • Expert and Tutoring Systems
    • Intelligent Agents
    • Knowledge Management
  • Learning and adaptation deals with changing a behavior from past experiences
  • Yet in order to learn we must choose among various alternatives, this is where knowledge management became an important goal in AI

Conception of Knowledge

5

Information Equality p = c p if and only if SI c

Austin = Capital of Texas

Knowledge example: Which is the best restaurant in Austin?

p => r (p IMPLIES r) judgment if City = Austin then the best restaurant is

An implication or a sound judgment (justified belief)

Product of experience or from a committed selection with the available information

A working hypothesis to be corroborated by the scientific method

A fact, true data (previously corroborated) o given as a postulate

Austin the capital of Texas ¿Is this Information or knowledge?

The Range of AI

7

Feedback and Cybernetics

Algorithms, Functions and Relations (Truth Processing)

Symbolical and Reasoning IF antecedent THEN consequence

Perceptua l

Learning and Adaptation

Common Sense and Concept Generation

AI Paradigms

for Knowledge Acquisition

  • Preprogrammed Intelligence
    • Game playing and Planning
    • Representation and Heuristic Search
    • Symbolic processing
    • Logic and Knowledge
  • Learning
    • Feedback and Adaptation
    • Connectionism
    • Neural Networks
    • Learning Automata
  • Selection
    • Genetic Algorithms
    • Evolutionary Programming
    • Classifier Systems
    • Genetic programming (^8)

Inflection Point in BRETAM

10

B R E T A M

  • While a breakthrough is being corroborated by researchers, a new breakthrough is found thus linking growth at the Inflection point (before d 2 fn/dt = 0 )
  • In this fashion breakthrough and research are combined
  • BRETAM phases occur horizontally (a new breakthrough) and vertically (at the same time)
  • Innovation requires that new products create new routines in work habits

B

B

B

B R

T

A

E

B R E T A M

A breakthrough reflects

a new form not seen before

R E T A M

AI history using the BRETAM model adapted from Gaines

11

Digital^ B^ R^ T circuits

E A M

Hardware B R E T A M

Autonomy B R E

Acquisition B R E T

Cooperation (^) B R E

M

A M

T A M

T A M

R E T A M

1940 1948 1956 1964 1972 1980 1988 1996 2004 2012 2020 2028 2036 2044 Generations^0 1 2

1988^ throw away

research

2004

Interaction B R E T A M

knowledge B R E T A

Software B R E T A M

Collaboration B

1972^ invention

1980^ innovative

low cost

(^1996) line 1972

Cognitive Sciences

Computing Sciences

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