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Transcript of 1 of 45 ARTIFICIAL INTELLIGENCE IS 340 CHANDRA S. AMARAVADI.
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ARTIFICIAL INTELLIGENCE
IS 340
CHANDRA S. AMARAVADI
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ARTIFICIAL INTELLIGENCE
IN THIS PRESENTATION
Introduction to AI Milestones & early work Machine Intelligence
The Nature of knowledgeKnowledge representationExamplesNeural nets Business & recent applications
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INTRODUCTION TO AI
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THE HISTORY OF AI (FYI)
•Alan Turing & test for intelligence -- 1950•AI as a field of study -- 1956•Lisp language -- 1958•Expert Systems -- 1965
•Dendral & Mycin•Small Talk, Prolog -- 1972•Fifth Generation Project -- 1981•Honda robot -- 1995•Stanford driverless car -- 2005
Major milestones
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Early research on AI focussed on:
LogicPerceptronsChessBlocks world (a world consisting of only blocks)
EARLY RESEARCH
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Generate and TestGenerate a possible solutionand test to see if it is the answer
Breadth-first Depth-first Heuristic Hill-climbing
SEARCH STRATEGIES
?
??
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DEFINING INTELLIGENCE
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Artificial Intelligence (AI)
DEFINITION
AI is concerned with the principles and mechanisms for achieving intelligent behavior in machines
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Artificialintelligence
Robotics
NLP VisionSystems
MachineLearning
ExpertSystems
BRANCHES OF AI
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NATURE OF INTELLIGENCE
Knowledge + Reasoning power
= Intelligence
Any other method of achieving intelligence?
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Top-down - build logical equivalents, e.g. LOGIC, Expert systems
Bottom-up - build physical equivalents, e.g. perceptrons, neural nets
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The Turing test: If a person interacting with an entity from a remote location is unable to judge whether he/she is dealing with a computer or a human, and the entity a machine, it is said to possess intelligence.
?
THE TEST FOR MACHINE INTELLIGENCE
Questions
Responses
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THE NATURE OFKNOWLEDGE
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KNOWLEDGE
facts,constraints,problems, goals,procedures.
Knowledge: information organized forproblem solving
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Two types of knowledge: Declarative – Knowledge about an object (size, shape etc.)Procedural – Knowledge about how to do something. (how to install memory)
THE NATURE OF KNOWLEDGE
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KNOWLEDGE REPRESENTATIONA Sampling of Knowledge
How to install a water pump The definition of a “field goal” Painters & styles from the modern era The process of becoming a GSA contractor The architectural differences between AMD &
Intel chips The meaning of “Lousiana report” in the context
of a faculty committee meeting.
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KNOWLEDGE REPRESENTATION
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KNOWLEDGE REPRESENTATION
Logic (Predicate logic) Frames Scripts Semantic nets (Snets) Rules
Knowledge representation is concerned withhow to encode knowledge
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IDENTIFY THESE AS EXAMPLESOF LOGIC, FRAMES, SCRIPTS…
sister_of(X,Y), bird_of_prey(X),father_of(robin, Y)father_of(robin,_)
EXAMPLE 1
EXAMPLE 2
is_a : dbmssoftware cost : $3,000License cost : check_with_vendor no of users : 2000 Max # of tables : 10,000Supports ODBC : Yes
If # of users > 300 then, license fee = $500
If # of users < 300 then, license fee = $300
EXAMPLE 3
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EXAMPLES OF KNOWLEDGEREPRESENTATIONS..
P PTRANS P to P.O.P ATTEND eyes to counterP MBUILD line positionP PTRANS P to lineP PTRANS M to XX PTRANS Stamps to P
EXAMPLE 4
Eagle
Bird
Is-a
1.5 m
MaxWingspan
20 Knots
MaxSpeed
Bird-of-prey
Is-a
EXAMPLE 5
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Based on associative memory “node” + “link” formalism nodes represent concepts or values links can be structural or descriptive
represent structure or characteristic
NOTES ON SEMANTIC NETS
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Origins in S-R paradigms Thought to be used by experts Have a IF…THEN… format
Note: S-R: stimulus/response
NOTES ON RULES
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A description (conceptual representation) of actions in a pre-defined situation Originated from film industry Consists of actors/props Act in predictable ways
NOTES ON SCRIPTS
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EXAMPLE OF LOGIC
facts:has_qualification(brad,3.2,620).has_qualification(jill,4.0,540).has_qualification(ted,3.5,320).has_qualification(matt,3.8, 600).
Predicates:select(X) :- has_qualification(X,GPA,GMAT),
GPA>3.2, GMAT>550;
Goals:select(brad)? jill? ted? matt?
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Identify whether the following types of knowledge are declarative or procedural and identify a suitable representation scheme, give rationale:
1. Admit students to MBA program if they have a gmat score of > 5502. A description of computing facilities at WIU. 3. A proof of the theorem that any triangle circumscribed by a semi-circle will always be a right angled triangle4. Instructions for assembling a PC5. Family relationships -- X and Y are the parents of P & Q; P has a maternal aunt Z. 6. Stages in a software life cycle -- analysis, design, implementation etc.
FOR DISCUSSION
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The brain
Dendrites
Neurons
Neural Net(a math model)
NEURAL NETS
Mathematical models to simulate neural models of the brain,Often used in applications requiring pattern recognition e.g.crime, fraud, intrusion detection etc.
eyesnose
hair color gait
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BUSINESS APPLICATIONS OF AI
Automated voice response Text mining Production applications
machine design robotics paper thickness
Scheduling of cranes Credit approval
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INDUSTRIAL APPLICATIONS OF AI
Driverless vehicles Facial recognition Crime prevention Pothole recognition Drones
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Can a machine ever have the intelligence of a human being?
Has Turing’s test been passed? Why did early researchers concentrate on Chess? If we make use of a frog’s brain to process stimuli, is that
an example of a Top-Down or a Bottom-up approach? What branch of AI does the work on perceptrons
resemble? What “hardware” item is essential equipment for vision
systems? Are robots useful in industry? How? If a machine is taking dictation, is it necessary to
understand the text or can it be done mechanically?
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The End!
Please note there are only 29 slides