1. What is Artificial Intelligence?
AI, Artificial Intelligence
Many definitions
No universal agreement
Based on different point of view, a different definition
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2. ???
Smarter
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3. Are computers the right kind of machine to be made intelligent?
Computers can be programmed to simulate any kind of machine.
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4. Are computers fast enough to be intelligent?
My own opinion is that the computers of 30 years ago were fast enough if only we knew how to program them. Of course, quite apart from the ambitions of AI researchers, computers will keep getting faster.
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5. Does AI aim to put the human mind into the computer?
Some researchers say they have that objective, but maybe they are using the phrase metaphorically. The human mind has a lot of peculiarities, and I'm not sure anyone is serious about imitating all of them.
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6. Different definitions of AI
Thought
Behavior
Human
Ideal
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7. ??? What is artificial intelligence (AI)? Why study AI?
How can you tell whether a machine or program is intelligent?
What kinds of things (if any) can be learned by a machine?
When can (should) machines replace human experts?
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8. What is AI?
AI definition was always debatable since the meaning of intelligence was not well-defined. Intelligence might be defined as the capacity to acquire and apply knowledge.
So AI was defined as:
AI is the study of ideas that enable computers to be intelligent.
AI is the part of computer science concerned with design of computer systems that exhibit human intelligence.
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9. What is AI?
From the above two definitions, we can see that AI has two major roles:
Study the intelligent part concerned with humans.
Represent those actions using computers.
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10. Goals of AI
To make computers more useful by letting them take over dangerous or tedious tasks from human
Understand principles of human intelligence
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11. More explanation Thought VS behavior Ideal?
Rational, reasonable and correct
Humans sometimes do incorrect things
Humans are sometimes irrational
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12. Human-like VS Rational?
A system thinks or acts like a human
Methods employed by humans
But, sometimes we even don’t know how??!!
A system thinks or acts rationally
Don’t care the methods, only care about the correctness of the result
Usually employ mathematical and logical models
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© Dr. Khalid Kaabneh, AAU

13. Acting humanly The Turing Test approach Intelligent behavior
a human questioner cannot tell if
there is a computer or a human answering his question, via teletype (remote communication)
The computer must behave intelligently
Intelligent behavior
to achieve human-level performance in all cognitive tasks
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© Dr. Khalid Kaabneh, AAU

14. Acting humanly These cognitive tasks include:
Natural language processing
for communication with human
Knowledge representation
to store information effectively & efficiently
Automated reasoning
to retrieve & answer questions using the stored information
Machine learning
to adapt (適應) to new circumstances
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© Dr. Khalid Kaabneh, AAU

15. The total Turing Test Includes two more issues: Computer vision
to perceive objects (seeing)
Robotics
to move objects (acting)
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© Dr. Khalid Kaabneh, AAU

16. Thinking humanly The cognitive modeling approach
To enable computer thinking like a human
We must have a precise theory of mind
Cognitive Science is dealing with the theory of mind
bringing together the theories of AI and psychology
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© Dr. Khalid Kaabneh, AAU

17. Thinking rationally The laws of thought approach
Logic is the laws of thought to govern the operation of mind.
Usually logic takes as inputs several premises and deduces a conclusion.
Example: If X and Y then Z (X ^ Y => Z)
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© Dr. Khalid Kaabneh, AAU

18. Acting rationally The rational agent approach
Given one’s beliefs (facts), one acts in order to achieve one’s goals
An agent is just something that perceives (感應) and acts
like a program: get inputs, and perform some outputs
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© Dr. Khalid Kaabneh, AAU

19. Acting rationally
Logic  only part of a rational agent, not all of rationality
Sometimes logic cannot reason a correct conclusion
At that time, some specific (in domain) human knowledge or information is used
Thus, it covers more generally different situations of problems
Compensate the incorrectly reasoned conclusion
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© Dr. Khalid Kaabneh, AAU

20. Acting rationally Study AI as rational agent – 2 advantages:
It is more general than using logic only
Because: LOGIC + Domain knowledge
It allows extension of the approach with more scientific methodologies
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© Dr. Khalid Kaabneh, AAU

21. The Foundation of AI Philosophy
At that time, the study of human intelligence began with no formal expression
Initiate the idea of mind as a machine and its internal operations
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© Dr. Khalid Kaabneh, AAU

22. The Foundation of AI
Mathematics formalizes the three main area of AI: computation, logic, and probability
Computation leads to analysis of the problems that can be computed
complexity theory
Probability contributes the “degree of belief” to handle uncertainty in AI
Decision theory combines probability theory and utility theory (bias)
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© Dr. Khalid Kaabneh, AAU

23. The Foundation of AI Psychology How do humans think and act?
Human thinking
Psychology
How do humans think and act?
The study of human reasoning and acting
Provides reasoning models for AI
Strengthen the ideas
humans and other animals can be considered as information processing machines
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© Dr. Khalid Kaabneh, AAU

24. The Foundation of AI Computer Engineering
How to build an efficient computer?
Provides the artifact (工具) that makes AI application possible
The power of computer makes computation of large and difficult problems more easily
AI has also contributed its own work to computer science, including: time-sharing, the linked list data type, OOP, etc.
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© Dr. Khalid Kaabneh, AAU

25. The Foundation of AI Control theory and Cybernetics
How can artifacts operate under their own control?
The artifacts adjust their actions
To do better for the environment over time
Based on an objective function and feedback from the environment
Not limited only to linear systems but also other problems
as language, vision, and planning, etc.
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© Dr. Khalid Kaabneh, AAU

26. The Foundation of AI Linguistics For understanding natural languages
different approaches has been adopted from the linguistic work
Formal languages
Syntactic and semantic analysis
Knowledge representation
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© Dr. Khalid Kaabneh, AAU

27. The history of AI Read it yourselves, if you feel interested in it
In short
AI has been born for over 50 years
Many different areas arise during this time
AI has evolved from laboratory research to an industry
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© Dr. Khalid Kaabneh, AAU

28. The state of the art What can AI do today? AI & Expert Systems
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29. AI Applications Autonomous Planning & Scheduling: Autonomous rovers.
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© Dr. Khalid Kaabneh, AAU

30. AI Applications Autonomous Planning & Scheduling:
Telescope scheduling:
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© Dr. Khalid Kaabneh, AAU

31. AI Applications Autonomous Planning & Scheduling: Analysis of data:
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32. AI Applications Medicine: Image guided surgery AI & Expert Systems
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33. AI Applications Medicine: Image analysis and enhancement
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34. AI Applications Transportation: Autonomous vehicle control:
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35. AI Applications Transportation: Pedestrian detection:
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36. AI Applications
Games:
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37. AI Applications
Games:
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38. AI Applications Robotic toys: AI & Expert Systems
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39. AI Applications Other application areas: Bioinformatics:
Gene expression data analysis
Prediction of protein structure
Text classification, document sorting:
Web pages, s
Articles in the news
Video, image classification
Music composition, picture drawing
Natural Language Processing .
Perception.
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© Dr. Khalid Kaabneh, AAU