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Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

4190.408 2016-Spring

Artificial Intelligence: Introduction

Byoung-Tak Zhang School of Computer Science and Engineering Seoul National University

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

4190.408 Artificial Intelligence

• Instructor: Prof. Byoung-Tak Zhang (btzhang@bi.snu.ac.kr)
• TA: Seong-Ho Son (shson@bi.snu.ac.kr) & Hyo-Sun Chun (hschun@bi.snu.ac.kr)
• Classroom: 302-107
• Time: Tue & Thu 11:00-12:15
• Objectives:

– To understand the theory and applications of artificial intelligence and cognitive science – To acquire the technical tools for building intelligent agents, such as Bayesian networks, deep neural networks, and reinforcement learning. – To understand the history and future prospects of artificial intelligence

• Textbook

– Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig, 2010.

• References

– A Tutorial on Learning with Bayesian Networks, David Heckerman – Cognitive Neuroscience: The Biology of the Mind, Third Edition, M.S. Gazzaniga, R.B. Ivry, and G.R. Mangun, Norton & Company, 2008. – Hypernetworks: A molecular evolutionary architecture for cognitive learning and memory, IEEE Computational Intelligence Magazine, 3(3):49-63, 2008.

http://bi.snu.ac.kr/Courses/4ai16s/4ai16s.html

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

4190.408 Artificial Intelligence

• Evaluation:

– two exams (50%) – two miniprojects (30%) – project presentation (10%) – participation in discussion (10%)

• Projects:

– Project 1: Bayesian networks – Project 2: Deep neural networks

• Practice

– Bayesian Network (3/15 & 3/17) – Deep Neural Network (T.B.A.)

• Topics

– Brain, Mind & AI – Bayesian Networks – Problem Solving and Heuristic Search – Knowledge Representation and Reasoning – Natural Language Processing – Logic, Symbolic AI, and Cognitive Science – Deep Neural Networks – Intelligent Agents – Cognitive Robots – Wearable AI – Human-level AI http://bi.snu.ac.kr/Courses/4ai16s/4ai16s.html

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

4190.408 Artificial Intelligence 2016-Spring

AI History and Highlights

Byoung-Tak Zhang School of Computer Science and Engineering Seoul National University

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

Brief History of AI

• Early enthusiasm (1950’s & 1960’s)

– Turing test (1950) – 1956 Dartmouth conference – Emphasize on intelligent general problem solving

• Emphasis on knowledge (1970’s)

– Domain specific knowledge – DENDRAL, MYCIN

• AI became an industry (late 1970’s & 1980’s)

– Knowledge-based systems or expert systems – Wide applications in various domains

• Searching for alternative paradigms (late 1980’s - early 1990’s)

– AI’s Winter: limitations of symbolic/logical approaches – New paradigms: neural networks, fuzzy logic, genetic algorithms, artificial life

• Resurge of AI (mid 1990’s – present)

– Internet, Information retrieval, data mining, bioinformatics – Intelligent agents, autonomous robots

• Recent trends:

– Probabilistic computation – Biological basis of intelligence – Brain research, cognitive science

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

Turing’s Dream of Thinking Machines (1950)

• Can machine think?
• Alan Turing proposes the Turing test to decide if a computer is exhibiting intelligent

behavior

– Turing, Alan M. "Computing machinery and intelligence." Mind (1950): 433-460.

• http://youtu.be/1uDa7jkIztw

Alan Turing (1912-1954)

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4190.408 Artificial Intelligence (2016-Spring)

Birth of AI (1956)

• Dartmouth Conference 1956: "Artificial Intelligence“ gained its name

–

• rganized by Marvin Minsky, John McCarthy and two senior scientists: Claude Shannon

and Nathan Rochester of IBM – proposal included this assertion: "every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it" – Proposal: http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html

Five of the attendees of the 1956 Dartmouth Summer Research Project on Artificial Intelligence reunited at the July AI@50

• conference. From left: Trenchard More, John McCarthy, Marvin

Minsky, Oliver Selfridge, and Ray Solomonoff. http://www.dartmouth.edu/~vox/0607/0724/ai50.html

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4190.408 Artificial Intelligence (2016-Spring)

Deep Blue (1997)

• IBM’s Deep Blue computer beats Garry Kasparov, the world chess champion.
• Deep Blue can evaluate 200 million chess positions per second
• http://youtu.be/y9UMt-8gfW8

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4190.408 Artificial Intelligence (2016-Spring)

DARPA Grand Challenge (2005)

• A Stanford vehicle wins the DARPA Grand Challenge
• Driving autonomously across the desert for 131 miles
• Racing Video: http://youtu.be/M2AcMnfzpNg
• Stanford Racing Team: http://cs.stanford.edu/group/roadrunner//old/index.html

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4190.408 Artificial Intelligence (2016-Spring)

DARPA Urban Challenge (2007)

• Tartan Racing (CMU+GM) claimed the $2 million prize
• 96 km urban area course, to be completed < 6 hours
• Challenge involves mission planning, motion planning, behavior generation,

perception, world modeling

• http://youtu.be/P0NTV2mbJhA

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4190.408 Artificial Intelligence (2016-Spring)

Google’s Driverless Car (2009)

• Uses artificial technology intelligence and makes decisions on its own (if mistake is

made it will alert driver)

– Artificial Intelligence / Computer Vision / GPS / Google Maps / Various Sensors

• Test Driving: http://youtu.be/X0I5DHOETFE
• Ted by Sebastian Thrun: http://youtu.be/r_T-X4N7hVQ

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4190.408 Artificial Intelligence (2016-Spring)

IBM Watson wons “Jeopardy!” (2011)

• Watson, a supercomputer built by IBM, defeated the two greatest-ever Jeopardy

champions

• Involves natural language processing, information retrieval, knowledge

representation and reasoning, and machine learning

• Jeopardy!: http://youtu.be/WFR3lOm_xhE
• CogniToy’s dinosaur connected to Watson: http://youtu.be/1Q2v2rIpjTg

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4190.408 Artificial Intelligence (2016-Spring)

Apple Siri: Personal Assistant (2011)

• an intelligent personal assistant and knowledge navigator which works as an

application for Apple's iOS

• adapts to the user's individual preferences over time and personalizes results, and

performing tasks such as finding recommendations for nearby restaurants, or getting directions

• http://youtu.be/8ciagGASro0

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4190.408 Artificial Intelligence (2016-Spring)

The Next 50 Years: Human-Level AI

• To achieve a true human-level intelligence, brain-like information

processing is required

Creative Adaptive Sociable Versatile Uncertain Inattentive Emotional Illogical

1 + 2 = 5 ! 100 < 10 ?

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

AI in Movies

• 2001 a Space Odyssey (1968)

– HAL-9000, human-level artificial assistant

• Bicentennial Man (1999)

– Android robot Andrew, household robot – Emphasize humanity of AI robot

• I, Robot (2004)

– Humanoid robots serve humanity by

• beying “Three Laws of Robotics”

– Inspired by Issac Asimov’s short-story collection in 1942

• A.I. (2006)

– AI robot with emotion

• Iron Man 3 (2008)

– JARVIS, an AI agent communicating and interacting with humans

• Her (2013)

– A haman falls in love with an AI computer

• Transcendence (2014)

– A supercomputer into which human consciousness is uploaded

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

What is Artificial Intelligence(AI)?

• Branch of computer science that is concerned with the automation
• f intelligent behavior
• Design and study of computer programs that behave intelligently
• Study of how to make computers do things at which, at the

moment, people are better

• Designing computer programs to make computers smarter
• Develop programs that respond flexibly in situation that were not

specifically

– e.g.) House-cleaning robots

• Perceive its surroundings
• Navigate on the floor
• Respond to events
• Decide what to do next
• Space exploration
• Synonyms of AI: machine intelligence

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4190.408 Artificial Intelligence (2016-Spring)

What is Artificial Intelligence(AI)?

• AI is a collection of hard problems which can be solved by humans and other living

things, but for which we don’t have good algorithms for solving.

–

• e. g., understanding spoken natural language, medical diagnosis, circuit design, learning, self-

adaptation, reasoning, chess playing, proving math theories, etc.

• Definition from R & N book: a program that

– Acts like human (Turing test) – Thinks like human (human-like patterns of thinking steps) – Acts or thinks rationally (logically, correctly)

• Some problems used to be thought of as AI but are now considered not

–

• e. g., compiling Fortran in 1955, symbolic mathematics in 1965, pattern recognition in 1970

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4190.408 Artificial Intelligence (2016-Spring)

Research Areas and Approaches

Artificial Intelligence Research

Rationalism (Logical) Empiricism (Statistical) Connectionism (Neural) Evolutionary (Genetic) Biological (Molecular)

Paradigm Application

Intelligent Agents Information Retrieval Electronic Commerce Data Mining Bioinformatics Natural Language Proc. Expert Systems Learning Algorithms Inference Mechanisms Knowledge Representation Intelligent System Architecture

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4190.408 Artificial Intelligence (2016-Spring)

Paradigms for Artificial Intelligence

Symbolic AI Rule-Based Systems Connectionist AI Neural Networks Evolutionary AI Genetic Algorithms Molecular AI: DNA Computing

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4190.408 Artificial Intelligence (2016-Spring)

Paradigms for Computational Intelligence

Symbolism Connectionism Dynamicism Hyper- interactionism

Metaphor Symbol system Neural system Dynamical system Biomolecular system Mechanism Logical Electrical Mechanical Chemical Description Syntactic functional Behavioral Relational Representation Localist Distributed Continuous Collective Organization Structural Connectionist Differential Combinatorial Adaptation Substitution Tuning Rate change Self-assembly Processing Sequential Parallel Dynamical Massively parallel Structure Procedure Network Equation Hypergraph Mathematics Logical, formal language Linear algebra, statistics Geometry, calculus Graph theory, probabilistic logic Space/time Formal Spatial Temporal Spatiotemporal

[Zhang, IEEE CIM, 2008]

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4190.408 Artificial Intelligence (2016-Spring)

4190.408 Artificial Intelligence 2015-Spring

AI History and Highlights: Appendix

Biointelligence Lab, SNU

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4190.408 Artificial Intelligence (2016-Spring)

Acting Humanly: Turing test

• Turing (1950) “Computing machinery and intelligence”:

– “Can machine think?”  “Can machine behave intelligently?” – Operational test for intelligent behavior: the Imitation Game – Predicted that by 2000, a machine might have a 30% chance of fooling a lay person for 5 minutes – Anticipated all major arguments against AI in following 50 years – Suggested major components of AI: knowledge, reasoning, language understanding, learning

• Problem: Turing test is not reproducible, constructive, or amenable

to mathematical analysis

[Stuart Russell's (Berkeley) course slides]

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4190.408 Artificial Intelligence (2016-Spring)

Thinking Humanly: Cognitive Science

• 1960s “Cognitive Revolution”: information-processing psychology

replaced prevailing orthodoxy of behaviorism

• Requires scientific theories of internal activities of the brain

– What level of abstraction? “Knowledge” or “Circuits”? – How to validate? Requires

• Predicting and testing behavior of human subjects (top-down)
• Direct identification from neurological data (bottom-up)
• Both approaches (roughly, Cognitive Science and Cognitive Neuroscience)

are now distinct from AI

• Both share with AI the following characteristic:

– The available theories do not explain (or engender) anything resembling human-level general intelligence

• Hence, all three fields share one principal direction!

[Stuart Russell's (Berkeley) course slides]

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4190.408 Artificial Intelligence (2016-Spring)

Thinking Rationally: Laws of Thought

• Normative (or prescriptive) rather than descriptive
• Aristotle (~ 450 B.C.): What are correct arguments/thought processes?
• Several Greek schools developed various forms of logic:

– notation plus rules of derivation for thoughts; – May or may not have proceeded to the idea of mechanization

• Direct line through mathematics and philosophy to modern AI
• Problems:

– Not all intelligent behavior is mediated by logical deliberation – What is the purpose of thinking? What thoughts should I have out of all the thoughts (logical or otherwise) that I could have?

[Stuart Russell's (Berkeley) course slides]

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Acting Rationally: The Rational Agent

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

given the available information

• Doesn’t necessarily involve thinking – e.g., blinking reflex – but thinking

should be in the service of rational action

• Aristotle (Nicomachean Ethics):

– Every art and every inquiry, and similarly every action and pursuit, is thought to aim at some good

[Stuart Russell's (Berkeley) course slides]

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4190.408 Artificial Intelligence (2016-Spring)

Brief history of AI - Golden years 1956-74

• Research:

– Reasoning as search: Newell and Simon developed a program called the "General Problem Solver". – Natural language Processing: Ross Quillian proposed the semantic networks and Margaret Masterman & colleagues at Cambridge design semantic networks for machine translation – Lisp: John McCarthy (MIT) invented the Lisp language.

• Funding for AI research:

– Significant funding from both USA and UK governments

• The optimism:

– 1965, Simon: "machines will be capable, within twenty years, of doing any work a man can do – 1970, Minsky: "In from three to eight years we will have a machine with the general intelligence of an average human being."

[Xiao-Jun Zeng’s (Univ. of Manchester) course slides]

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

Brief history of AI - The first AI winter

• The first AI winter 1974−1980:

– Problems

• Limited computer power: There was not enough memory or

processing speed to accomplish anything truly useful

• Intractability and the combinatorial explosion. In 1972 Richard

Karp showed there are many problems that can probably only be solved in exponential time (in the size of the inputs).

• Commonsense knowledge and reasoning. Many important

applications like vision or natural language require simply enormous amounts of information about the world and handling uncertainty.

– Critiques from across campus

• Several philosophers had strong objections to the claims being made

by AI researchers and the promised results failed to materialize

– The end of funding

• The agencies which funded AI research became frustrated with the

lack of progress and eventually cut off most funding for AI research.

[Xiao-Jun Zeng’s (Univ. of Manchester) course slides]

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4190.408 Artificial Intelligence (2016-Spring)

Brief history of AI - Boom 1980–1987

• Boom 1980–1987:

– In the 1980s a form of AI program called "expert systems" was adopted by corporations around the world and knowledge representation became the focus of mainstream AI research

• The power of expert systems came from the expert knowledge using

rules that are derived from the domain experts

• In 1980, an expert system called XCON was completed for the Digital

Equipment Corporation. It was an enormous success: it was saving the company 40 million dollars annually by 1986

• By 1985 the market for AI had reached over a billion dollars

– The money returns: the fifth generation project

• Japan aggressively funded AI within its fifth generation computer

project (but based on another AI programming language - Prolog created by Colmerauer in 1972)

• This inspired the U.S and UK governments to restore funding for AI

research

[Xiao-Jun Zeng’s (Univ. of Manchester) course slides]

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

Brief history of AI - the second AI winter

• the second AI winter 1987−1993

– In 1987, the Lisp Machine market was collapsed, as desktop computers from Apple and IBM had been steadily gaining speed and power and in 1987 they became more powerful than the more expensive Lisp machines made by Symbolics and others – Eventually the earliest successful expert systems, such as XCON, proved too expensive to maintain, due to difficult to update and unable to learn. – In the late 80s and early 90s, funding for AI has been deeply cut due to the limitations of the expert systems and the expectations for Japan's Fifth Generation Project not being met – Nouvelle AI: But in the late 80s, a completely new approach to AI, based on robotics, has bee proposed by Brooks in his paper "Elephants Don't Play Chess”, based on the belief that, to show real intelligence, a machine needs to have a body — it needs to perceive, move, survive and deal with the world.

[Xiao-Jun Zeng’s (Univ. of Manchester) course slides]

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4190.408 Artificial Intelligence (2016-Spring)

Brief history of AI - AI 1993−present

• AI achieved its greatest successes, albeit somewhat

behind the scenes, due to:

– the incredible power of computers today – a greater emphasis on solving specific subproblems – the creation of new ties between AI and other fields working on similar problems – a new commitment by researchers to solid mathematical methods and rigorous scientific standards, in particular, based probability and statistical theories – Significant progress has been achieved in neural networks, probabilistic methods for uncertain reasoning and statistical machine learning, machine perception (computer vision and Speech), optimisation and evolutionary computation, fuzzy systems, Intelligent agents.

[Xiao-Jun Zeng’s (Univ. of Manchester) course slides]

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4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: 2001 a Space Odyssey

• 2001 a Space Odyssey (1968, Stanley Kubrick)
• HAL-9000, 공상과학 영화 속의 인간수준 인공지능 비서

– 우주선 Discovery의 관제와 승무원 보호를 담당 – 현재 상황을 인식하고 추론, 미래를 예측하여 행동을 수행 – 미래를 예측하고 이를 바탕으로 행동하는 능력은 인간 수준 인공지능의 핵심적인 자질 [Movie clip] [HAL 9000: AI system]

[Byoung-Tak Zhang’s Doosan seminar slides]

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4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: Star Trek

• Star Trek (1973 ~ 2013)
• Lieutenant Commander Data

– One of main characters of Star Trek – Artificial intelligence android with self-consciousness

Cold-minded Android Human-like Android Continuously learns how human acts [Movie clip] [Data: AI android]

[Byoung-Tak Zhang’s Doosan seminar slides]

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4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: Bicentennial Man

• Bicentennial Man (1999)
• Android robot Andrew

who is purchased as a household robot

• Emphasize “humanity”
• f AI robot

– If a robot spends enough time around humans, can he learn to become one

• f them?

– Emotion, Creativity, Curiosity, Achievement Need, Love …

[Byoung-Tak Zhang’s Doosan seminar slides]

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4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: I, Robot

• I, Robot (2004)
• What is intelligence?

– Information processing – Creativity, dreaming, free will, spirit – An exceptional result  just error? – A.I. & robot: indispensability for each other

• Three laws of robotics (Isaac Asimov, 1942)

– These rules might occur unexpected problems. – A.I. with exceptional results need to be studied.

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm. 2. A robot must obey the orders given to it by human beings, except where such orders would conflict with the First Law. 3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.

[Movie clip]

[Byoung-Tak Zhang’s Doosan seminar slides]

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: A.I.

• A.I. (2006)
• AI robot with emotion

– “David” – Perception, cognition, and action like humans – Influence of the emotion on thinking – Active goal setting and planed behavior – Learning and self-improving from the experiences

[Byoung-Tak Zhang’s Doosan seminar slides]

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: Iron Man 3

 Iron Man 3 (2008)  J.A.R.V.I.S.

• AI agent communicating

and interacting with humans

• Information gathering from

sensors and internet

• Priority
• Speech recognition
• Context-aware
• Object recognition
• Gesture recognition
• Active learning
• Future prediction based

from the data

[Byoung-Tak Zhang’s Doosan seminar slides]

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4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: Surrogate (2009)

• Surrogate (2009)
• Artificial lifeforms

that can link up with humans

– Mankind stays at home and operates surrogates – Go out into the world without having to deal with dangers

• Surrogate does not

have AI

• kind of another body

like avatar

[Byoung-Tak Zhang’s Doosan seminar slides]

Bio Intelligence

4190.408 Artificial Intelligence (2016-Spring)

AI in Movies: Her

• Her (2013)
• A human falls in love with

an AI computer

• Human-like intelligence

– Personal assistant, companion, lover, composer, coach – Interact with us, learn with us and ultimately express sentiments and creativity

 Learn

• Concept
• Understanding
• Reasoning

 Creative

• Artistic
• Musical

 Interact

• Cognition
• Recognition
• Consciousness

 Express

• Perception
• Self-aware
• Communication

Human AI System

[Byoung-Tak Zhang’s Doosan seminar slides]