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Artificial Intelligence

CS 404

Berrin Yanikoglu

To Know

• Basic history of AI – Know some of the important events or at least what

happend in different eras

• Difficulty of defining intelligence and some of the attempts– Fleeting nature of the definition– Difference of humanly/rational thinking/acting

• Turing test• Rational agents• … 2

Course Info• Webpage: – http://people.sabanciuniv.edu/~berrin/cs404/ • for info, expectations, lecture notes, assignments, ...

– Linked from SuCourse

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On May 12th, 1997, thebest chess player in the world, Gary Kasparov,lost a six-game chessmatch to a computernamed “Deep Blue 2”

What was so significantabout this event?

Being able to program a computer to defeat a Grand Master levelchess player had been a long-standing goal of the science of artificial intelligence - and now it has been achieved

What is Artificial Intelligence?Intelligence is difficult to define and understand, even for philosophers and psychologists who spend their lives studying it. But this elusive quality is, to many people, the characteristic that sets humans apart from other species

“What is intelligence, anyway? It is only a word that people use to name those unknown processes with which our brains solve problems we call hard. But whenever you learn a skill yourself, you are less impressed or mystified when other people do the same.

This is why the meaning of “intelligence” seems so elusive: It describes not some definite thing but only the momentary horizon of our ignorance about how minds might work.”

- Marvin Minsky, AI researcher

What is Artificial Intelligence?Smart programs?

– Not really. Studying what is possible and underlying theories are very important.

– How does a slow, tiny brain (biological or electrical) perceives, understands, and manipulates a complex world?

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Studying AI • Started out in 1950s– The Dartmouth meeting in 1956

• Turned out much more difficult than anyone had imagined

• Currently encompasses a large variety of subfields, – from general areas such as perception and logical reasoning

to – specific tasks such as playing chess, writing poetry…– bringing together philosophy, logic, computer science,

cognitive science and cognitive neuroscience7

What is AI? So it’s not surprising that defining artificial intelligence (AI) is hard. In general,

artificial intelligence is the field of science devoted to making computers perceive, reason, and act in ways that have, until now, been reserved for human beings.

4 types of historical definitions: acting or thinking humanly acting or thinking rationally

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Thinking Humanly: Cognitive Science

• How do humans think?– Requires scientific theories of internal activities of the brain

• What level of abstraction? ``Knowledge'' or ``circuits''?• How to validate?

– Bring together computational models from AI and experimental techniques from psycho-physics to model the human mind

• 1) Predicting and testing behavior of human subjects (Cognitive Science; top-down)

• 2) Direct identification from neurological data (Cognitive Neuroscience; bottom-up)– Both approaches are now distinct from AI

– Most of the machinery of the human mind is not available to our conscious experience

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Thinking Logically• Let’s give up imitating the human thinking process, but try to

achieve logical thinking

• Laws of formal logic to formalize the thinking process– Socrates is a man; All men are mortal => Socrates is mortal

• Difficulties:– How to take informal knowledge and state in formal terms especially

when knowledge is less than 100% certain

– Even problems with just a few dozen facts can be prohibitive

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Acting Humanly - Turing Test

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Acting Humanly - Turing Test• UCSD Turing Page: http://cogsci.ucsd.edu/~asaygin/tt/ttest.html

• Captchas– Tests to identify humans from bots on the Internet, to deny services to webcrawlers or

spammers

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Acting Humanly - Turing Test• Chatterbots:

– One of the most complex (and entertaining!) chatter bots are at: http://www.simonlaven.com/

• choose complex chatterbots, choose Barry, go to downloads and then choose CGI talk (this year they dont have the online CGI talk, and the downloaded program didnt work for me)

– Or this one works with no downloads: The ALICE Foundation• ...• Human: You sound pretty smart• ALICE: In what way do I sound like that?

Human: never mind, hey, how is the weather?ALICE: Oh well thanks for trying to explain it to me anyway. You've got my full attention. Sunny.Human: where are you?ALICE: I am in Dr. Richard S. Wallace's computer in Oakland, California. Where are you?Human: i am in istanbul, do you know where it is?ALICE: Tell me a little about your life in istanbul do me know where it is.

• ...

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Acting Rationally

• Rationality: ideal concept of intelligence

• Rational behavior: doing the right thing– that which is expected to maximize goal achievement, given the

available information– Reflexes do not necessarily involve thinking---e.g., blinking reflex, but

they are rational– Thinking should be in the service of rational action

• Caveat: computational limitations make perfect rationality unachievable

design best program for given machine resources

• We will emphasize rational agents in this course.

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Why do we want artificial intelligence?

• To relieve our mental labour, just as machines relieved our physical labour last century

• It should make the machines themselves easier to use

• It might give some insight into the workings of our own minds

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History of AI• 1943 McCulloch and Pitts: Artificial Neuron Model • 1950 Turing's ``Computing Machinery and Intelligence'‘

• 1950s Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist (proving theorems), Gelernter's Geometry Engine, Shannon and Turing writing chess programs

– Shortage of computer times => Development of time sharing (=> DEC)– Creation of LISP (McCarthy)

• 1956 Dartmouth meeting: ``Artificial Intelligence'' coined• 1965 Robinson's complete algorithm for logical reasoning resolution method

• 1960s Early development of knowledge-based systems; Minsky’s microworlds (blocks as home to various projects: vision, planning, nat. Lang. Understanding, ...)

– ANALOGY program (what is this figure most similar to?)– Algebra STUDENT program (one egg costs ... How much does twenty eggs cost?)

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History of AI• 1966--74 Dose of Reality

• Very little domain knowledge:– Swithing from one domain to another, the programs failed miserably

• AI discovers computational complexity– Early programs worked by representing the basic facts and trying out a

series of steps to solve the problem which was only tractable within micro worlds; NP-completeness showed that scaling up to larger problems was not always viable

• Neural network research almost disappears

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History of AI

• 1980--88 Expert systems industry booms– After all, they work, even if in limited domains

– An expert system is a software designed to replicate the decision-making process of a human expert, within a narrow topic. At the heart of every expert system is a knowledge base representing ideas from the specific field of expertise

– A knowledge-based system derives knowledge from experts as well as other sources like government regulations, statistical databases, company guidelines, etc.

– In practice, the terms expert system and knowledge-based system are often used interchangeably

• While a database contains only facts, a knowledge base also contains a system of if-then rules for determining and changing the relationships between those facts

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Digression: Expert Systems•Expert systems are widely used in many different areas:

American Express uses one to automate checking for fraud and misuses of its no-limit credit card. This has to be done in 90 secs while the customer waits, and the cost of an error can be high

DENDRAL, an expert system that examines the spectroscopic analysis of an unknown chemical compound and predicts its molecular structure

DEC’s XCON configures complex computer systems. It reportedly does the work of > 300 human experts, with fewer mistakes

PIERS, an expert system used to diagnose blood samples in St Vincent Hospital, Sydney

...

•Current success is in reasonably narrow topics, eg mineral prospecting, medical diagnoses, air traffic control, etc. But the real goal is to build something that has a broad understanding of the world - which requires common sense

History of AI• 1988--93 Expert systems industry start losing its power

• Successful only in very narrow domains• Building a successful expert system is much more than simply

buying a reasoning system and filling it with rules

• 1985--95 Neural networks return to popularity

• 1988-- With strengthened foundations, AI becomes hot again - resurgence of probabilistic and decision-theoretic methods, genetic algorithms, belief networks,...

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Current State• Which of the following can be done at present!?

– Play a decent game of table tennis– Drive along a curving mountain road– Drive in the center of Istanbul– Play a decent game of bridge– Discover and prove a new mathematical theorem– Write an intentionally funny story– Give competent legal advice in a specialized area of law– Translate spoken English into spoken Swedish in real time

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Current State• Which of the following can be done at present!?

– Play a decent game of table tennis– Drive along a curving mountain road– Drive in the center of Istanbul– Play a decent game of bridge– Discover and prove a new mathematical theorem– Write an intentionally funny story– Give competent legal advice in a specialized area of law– Translate spoken English into spoken Swedish in real time

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Current State

• Limited domain speech/natural language understanding programs

• Chess playing programs (machines)

• Medical expert systems challenging doctors

• ...

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Artificial Intelligence and the Humans

•What does the advent of the intelligent machine mean for human beings?

•Are artificial intelligences just extensions of human intelligence?

•When AARON creates a drawing, who is the artist, Cohen or AARON?

•When expert systems make decisions, who is responsible? the user, the programmer, the software company, or somebody else?

•Should we think of intelligent machines as some new sort of life, one with which we must now share the world?

•Could AIs be our evolutionary successors?

•How will AI affect our own sense of self?

•AI is beginning to force us to confront these hard philosphical questions…

Syllabus• http://people.sabanciuniv.edu/~berrin/cs404/syllabus.htm

• In short (AIMA 3rd ed.)– Introduction:

• Chapters 1-2– Problem Solving

• Chapters 3-6– Knowledge and Reasoning

• Chapters 7-9– Planning:

• Skipped with just a brief overview– Uncertain Knowledge and Reasoning

• Chapters 13,14,16; skip 15 and 17– Learning

• overview + one classification method (decision trees)– Communicating, Perceiving, Acting

• overview + one problem in computer vision– Conclusions

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Seeing, Hearing and UnderstandingAn intelligent computer must be able to recognize its surrounding environment and adapt to changes in it. To do this it must be able to “see” and “hear” what’s going on

Computer vision is the capability of a computer to mimic the ways that human brains process and interpret light waves to produce a model of reality. Though it’s very easy for people to do that, it’s very difficult for computers to do build and update their models

Hearing, Seeing and UnderstandingThe ability of a computer to recognize the speech of a user and take action based on the words spoken is called speech recognition or voice recognition. The computer matches spoken words against stored speech patterns to determine what was said

Natural language processing is the ability of a computer to build knowledge representations corresponding to the meaning in sentences made up of recognized words. This is very difficult, because human language is full of ambiguities, vagueness and depends on a lot of commonsense knowledge of the world

Machine Learning•We’ve seen how difficult collecting and maintaining knowledge is. If there was a lot, it could be impossible to do by hand

•It would help if the machine could build up its own knowledge from experiences in the world, like a child learning how to walk. The ability of the machine to discover knowledge from observations of the world is called machine learning

For example, some of the best game-playing programs learn from past experiences. If a move pays off, a learning program is more likely to use that (or similar moves) in future games. If a move results in a loss, the program will remember to avoid similar moves

Robots - AI EmbodiedRobots - AI Embodied

• Japanese companies such as Honda, Fujitsu and Sony are racing to develop humanoids

• The Honda ASIMO (right) is a good example

• Improved walking stability over earlier models

• Smaller size is about marketing - and Robocup eligibility

• Intelligence quite limited - some commands sent by remote control

• Simple voice recognition functions trigger pre-programmed actions

• Will cost about the same a luxury car