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1 of 45 ARTIFICIAL INTELLIGENCE IS 340 CHANDRA S. AMARAVADI.

Jan 11, 2016

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Page 1: 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