Artificial Intelligence And Neural Networks Presentation
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02-03-2010, 09:32 PM



.ppt   01)Introduction.ppt (Size: 2.07 MB / Downloads: 448)
Artificial Intelligence & Neural Networks


Presented By:
Lim Kyungeun


What is AI?

Acting humanly: The Turing Test approach
Thinking humanly: The cognitive modeling approach
Thinking rationally: The laws of thought approach
Acting rationally: The rational agent approach
The Goals of AI
Example of AI in Real World
The State of The Art

]Thinking humanly: The cognitive modeling approach

The exciting new effort to make computers think ¦ machines with minds, in the full and literal sense. (Haugeland, 1985)

Cognitive science

Construct theories of the human mind.
We need to get inside the actual workings of human mind.
Now distinct from AI
The computer needs the capabilities such as
Natural language processing: to communicate (common sense)
Knowledge representation: to store information
Automated reasoning: to use the stored information and draw conclusions
Machine learning: to adapt to new circumstances

To pass the total Turing Test (physical simulation of a person)
Computer vision: to perceive objects
Robotics: to moveIs the human being the only model ?
Not necessarily (ex, bird and airplane example)
It is often possible to construct a computer program that meets some performance standard for a particular task.

Thinking rationally: The laws of thought approach

The study of the computations that make it possible to perceive, reason, and act. (Winston, 1992)
Correct inference
Mathematical logic (syntax vs. semantics)
Example: Aristotleâ„¢s syllogisms
Socrates is a man.
All men are mortal.
Socrates is mortal.
Two main problems
Cannot formally represent all knowledge.
A big difference between being able to solve a problem in principle and doing so in practice.
practically intractable


Acting rationally: The rational agent approach
Computational Intelligence is the study of the design of intelligent agents. (Poole et al., 1998)

AI . . . is concerned with intelligent behavior in artifacts. (Nilsson, 1998)Advantages
More general than the laws of thought approach.
Correct inference is not all of rationality
Limited rationality: acting appropriately when computational resources are not enough
There are ways of acting rationally that cannot be reasonably said to involve inference.
More amenable to scientific development than approaches based on human behavior or human thought.
The standard of rationality is clearly defined and completely general.
We concentrate on general principles of rational agents, and on components for constructing them


The Goals of AI

Engineering goal:
To solve real world problems.
(or to build machines for that)

Scientific goal:

To understand and explain intelligence.
(in machines or humans)


Example of AI in Real World

Biometric identification
Speech recognition and understanding and synthesis
Image understanding
e.g. face, eye, fingerprints, voice pattern
Compare data from person at door with stored library
Consumer marketing
Algorithms (data mining) search data for pattern
Predicting the Stock Market
Given the past, predict the future
We can use learning algorithms to learn a predictive model from historical data

The State of The Art

Autonomous planning and scheduling:
To control the scheduling of operations for a spacecraft
Game playing
Autonomous control:
Computer vision system trained to steer a car
Diagnosis
Logistics planning:
Automated logistics planning and scheduling for transportation
Robotics
Language understanding and problem solving
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