Dr. Mike Bowman Computer Science and Information Systems Department ACM Spring 2014.

Dr. Mike BowmanComputer Science and Information

Systems DepartmentACM Spring 2014

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Acknowledgements

Learning Agents Center and Computer Science Department

George Mason Universitylalab.gmu.edu

Association for the Advancement of Artificial Intelligence (AAAI)

www.aaai.org

AI – Thinking Machines?

Are you smarter than a machine?

Can machines think?

What is Skynet?

http://www.youtube.com/watch?v=DEtrzdGSXCU

What is the Matrix?http://www.youtube.com/watch?v=WnEYHQ9dscY

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How Smart Are You?

Can youcount the cars in this

picture?

Can you estimate the time of day in

this picture?

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How Smart Are You?

Can you count the Distribution of letters in a book?

Add one thousand4-digit numbers?

Match finger prints?

Search a list of a million values for duplicates?

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AI – What is Real?

Are you smarter than a machine?

Who was Deep Blue?http://www.youtube.com/watch?v=NJarxpYyoFI

Who is Watson?http://www.youtube.com/watch?v=o6oS64Bpx0g&feature=related

What is the Singularity?http://www.ted.com/talks/ray_kurzweil_announces_singularity_university.html

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Current Reality?

The current reality is that computers and some robots can do some really remarkable complex tasks, and in some cases do them better than humans. But at the same time, no one is yet arguing that machines are conscious or possess human-level intelligence.

On the other hand, since no one seems to really understand much about how the human brain works, or what the basis of consciousness is (although some are working on it), the state of AI today is still pretty impressive.

Thinking Machines

Artificial intelligence (AI)

The study of computer systems that attempt to model and apply the intelligence of the human mind

For example, writing a program to pick out objects in a picture

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Where do you often interact with AI?

AI in Games

The Good, the bad, and the ugly (actually the reality)

Most modern computer/video games include “intelligent” opposition – AI

http://www.youtube.com/watch?v=gr58eWO5Dgo

http://www.youtube.com/watch?v=tFxbakAamsc

http://www.youtube.com/watch?v=Ux0TZqEAiK0

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The Turing TestTuring test

A test to empirically determine whether a

computer has achieved intelligence

Alan TuringAn English mathematician wrote a landmark paper in 1950 that asked the question: Can machines think?He proposed a test to answer the question "How will we know when we’ve succeeded?"

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The Turing Test

In a Turing test, the interrogator must determine which responses are from the computer and which are from the human

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The Loebner Prize

Loebner prizeThe first formal instantiation (1991) of the Turing test,held annually

ChatbotsA program designed to carry on a conversation with a human user

http://www.loebner.net/Prizef/loebner-prize.html

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Some Focus Areas of AI• Knowledge representation – represent

knowledge so that a computer can apply it

• Expert Systems – computer systems that embody the knowledge of human experts

• Neural networks – computer systems that mimic the processing of the human brain

• Natural language processing – computers that can understand and use human speech

• Robotics – systems that can complete physical actions to solve problems

14Just a small sample of AI topics!

Knowledge Representation

How can we represent knowledge?•We need to create a logical view of the

data, based on how we want to process it•Natural language is very descriptive, but

doesn’t lend itself to efficient processing•Semantic networks and search trees

are promising techniques for representing knowledge

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Semantic Networks

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Intelligent agents contain a representation of an application domain, where information about the domain (objects, relations, classes, laws, actions) are represented as symbolic expressions.

This mapping allows the agent to reason about the domain by performing reasoning processes in the domain model, and transferring the conclusions back into the application domain.

represents

RULE x,y,z OBJECT, (ON x y) & (ON y z) (ON x z)

ONCUP1 BOOK1 ON TABLE1

CUP BOOK TABLE

INSTANCE-OF

OBJECT

SUBCLASS-OF

Model of the Domain

ONTOLOGY

2005, G.Tecuci, Learning Agents Center

Knowledge Representation and Reasoning

17Application Domain

If an object is on top of another object that is itself on top of a third object then the first object is also on top of the third object.

Knowledge Base = Ontology + Rules

ONTOLOGY FRAGMENT

Main condition?O1 is PhD_advisor

has_as_employer ?O4 has_as_position ?O5

?O2 is PhD_student?O3 is research_area?O4 is university?O5 is tenured_position

Except when condition?O1 is person

is_likely_to_move_to ?O6?O6 is employer

IF: Determine whether ?O1 can be a PhD advisor for ?O2 in ?O3.

THEN: Determine whether ?O1 would be a good PhD advisor for ?O2 in ?O3.

REASONING RULE

Determine whether John Smith can be a PhD advisor for Tom Even in Artificial Intelligence.

PROBLEM SOLVING

TASK

Ph.D. student

facultymemberstaff

member

professor

studentuniversityemployee

person

subconcept-of

subconcept-of

subconcept-of subconcept-of

subconcept-of

M.S. student

B.S. studentinstructor

graduatestudent

undergraduatestudent

fullprofessor

associateprofessor

assistantprofessor

subconcept-of

subconcept-of

PhD_advisor

18 2005, G.Tecuci, Learning Agents Center

Search Trees

Search tree

A structure that represents alternatives in adversarial situations such as game playing

The paths down a search tree represent a series of decisions made by the players

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Search Trees

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Search Trees

Techniques for pruning search space

Depth-first A technique that involves the analysis of selected paths all the way down the tree Breadth-first A technique that involves the analysis of all possible paths but only for a short distance down the treeBreadth-first tends to yield the best results

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Search Trees

Depth-first and breadth-first searches22

Expert Systems

Knowledge-based system Software that uses a specific set of information, from which it extracts and processes particular pieces

Expert system A software system based on the knowledge of human experts; it is

– Rule-based system• A software system based on a set of if-then rules

– Inference engine• The software that processes rules to draw conclusions

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Expert Systems

Gardner Expert System Example24

Expert Systems

Named abbreviations that represent conclusions

NONE – apply no treatment at this timeTURF – apply a turf-building treatmentWEED – apply a weed-killing treatmentBUG – apply a bug-killing treatmentFEED – apply a basic fertilizer treatmentWEEDFEED – apply a weed-killing and

fertilizer combination treatment

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Expert SystemsBoolean variables needed to represent state of the lawn

– BARE: the lawn has large, bare areas

– SPARSE: the lawn is generally thin

– WEEDS: the lawn contains many weeds

– BUGS: the lawn shows evidence of bugs

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Expert Systems

Some rules– if (CURRENT – LAST < 30) then NONE

– if (SEASON = winter) then not BUGS

– if (BARE) then TURF

– if (SPARSE and not WEEDS) then FEED

– if (BUGS and not SPARSE) then BUG

– if (WEEDS and not SPARSE) then WEED

– if (WEEDS and SPARSE) then WEEDFEED

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Expert SystemsOperation of expert systems can involve dialog

between a human and the system– System: Does the lawn have large, bare

areas?– User: No– System: Does the lawn show evidence of

bugs?– User: No– System: Is the lawn generally thin?– User: Yes– System: Does the lawn contain significant

weeds?– User: Yes– System: You should apply a weed-killing and

fertilizer combination treatment.28

Neural Networks

Artificial neural networks

An attempt to represent knowledge, and solve problems, with approaches that mimic the way the human brain works.

– often involves probabilities and statistics to determine (guess?) most likely outcomes.

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Natural versus Artificial

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http://faculty.washington.edu/chudler/color/pic1an.gif

http://research.yale.edu/ysm/images/78.2/articles-neural-neuron.jpg

Biological Artificial

Natural Language Processing

Three basic types of processing occur during human/computer voice interaction

Voice synthesis

Using a computer to create the sound of human speech

Voice recognition

Using a computer to recognizing the words spoken by a human

Natural language comprehension

Using a computer to apply a meaningful interpretation to human communication

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Natural Language Comprehension

What does this sentence mean?

Time flies like an arrow.– Time goes by quickly– Time flies (using a stop watch to measure

speed of a fly) as you would time an arrow– Time flies (a kind of fly) are fond of an arrow

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Crazy?Maybe, but a computer has great

difficulty with understanding context.

Imagine a simple rule such as:

A + B + C = D

It could represent the rule an agent uses to identify a cat:(4 legs) + (fur) + (meow) = CAT

A sophisticated agent “learns.”

If presented with a dog [(4 legs) + (fur) + (bark) = ??]

It should recognize it as not being a cat, and ask a human trainer for clarification, resulting in a new rule:

A + B + E = F (4 legs) + (fur) + (bark) = DOG

Rules and Machine Learning

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Start with the same rule:

A + B + C = D

It could represent the rule an agent uses to identify a cat:(4 legs) + (fur) + (meow) = CAT

A very sophisticated agent “learns rapidly.”

It might generalize the rule to (~A) + (~B) + (~C) = CAT

It will occasionally “miss-fire” (ID a dog as a cat) by misusing the generalized rule, but given “supervision and corrections” by humans (explaining why it misused the rule), it will learn rapidly.

Rules and Machine Learning

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• Deep Blue was a special purpose computer that was able to calculate nearly a quarter of a billion chess positions per second. It lost a match with a world champion in 1996, but defeated that same champion in 1997.

• Certain endgame arrangements were always thought to represent a draw -- no human had ever seen a way to win. Deep Blue and other chess playing programs have found ways to win some of these games.

• The Asian game "go" will not succumb to such brute force methods -- there are simply too many possible moves for even the most powerful current and planned supercomputers. Instead, "real" AI will be needed -- intelligence based on pattern recognition, "insight," and strategy.

IBM’s Deep Blue

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State of the Art in AI

IMB’s Watson – Jeopardy Champion

Research question: Can a system be designed that applies advanced data management and analytics to natural language in order to uncover a single, reliable insight — in a fraction of a second?

Watson beat human champions in Jeopardy, and is now being used to investigate human health issues.

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State of the Art in AI

The DARPA Grand Challenge tasked entrants to build an autonomous robotic vehicle that could successfully navigate a long, complex course, without human intervention.

None of the entrants in the 2004 Grand Challenge 1 completed more than 10 miles of the 100 mile course.

DARPA Grand Challenge

State of the Art in AI

In the 2005 Grand Challenge II, 5 of the 20+ entrants completed the 132 mile race through the Mojave Desert, well under the 10 hour time limit.

The 2007-2010 Urban Challenge was to drive through an urban setting. It was successfully completed by multiple entrants! 37

The latest DARPA event is called the Robotics Challenge and tasks entrants to build an all-terrain autonomous device that can successfully navigate through complex obstacles like stairs, without human intervention AND successfully complete missions that are hazardous to humans.

DARPA Robotics Challenge

State of the Art in AI

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Where has a famous AI system and someone named Bowman crossed paths?

http://www.youtube.com/watch?v=ARJ8cAGm6JE

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AI versus Bowman

CSC370 – Fall 2014Tuesday and Thursday – 2:00-3:15 PM