Artificial Intelligence: Introduction

Transcription

1 Spring Artificial : Introduction Byoung-Tak Zhang School of Computer Science and Engineering Seoul National University Artificial (2016-Spring)

2 Artificial Instructor: Prof. Byoung-Tak Zhang TA: Seong-Ho Son & Hyo-Sun Chun Classroom: 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 : A Modern Approach, Stuart Russell and Peter Norvig, References A Tutorial on Learning with Bayesian Networks, David Heckerman Cognitive Neuroscience: The logy of the Mind, Third Edition, M.S. Gazzaniga, R.B. Ivry, and G.R. Mangun, Norton & Company, Hypernetworks: A molecular evolutionary architecture for cognitive learning and memory, IEEE Computational Magazine, 3(3):49-63, Artificial (2016-Spring)

3 Artificial 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 Artificial (2016-Spring)

4 Artificial 2016-Spring AI History and Highlights Byoung-Tak Zhang School of Computer Science and Engineering Seoul National University Artificial (2016-Spring)

5 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 logical basis of intelligence Brain research, cognitive science Artificial (2016-Spring)

6 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): Alan Turing ( ) Artificial (2016-Spring)

7 Birth of AI (1956) Dartmouth Conference 1956: "Artificial gained its name organized 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: Five of the attendees of the 1956 Dartmouth Summer Research Project on Artificial reunited at the July AI@50 conference. From left: Trenchard More, John McCarthy, Marvin Minsky, Oliver Selfridge, and Ray Solomonoff Artificial (2016-Spring)

8 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 Artificial (2016-Spring)

9 DARPA Grand Challenge (2005) A Stanford vehicle wins the DARPA Grand Challenge Driving autonomously across the desert for 131 miles Racing Video: Stanford Racing Team: Artificial (2016-Spring)

10 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 Artificial (2016-Spring)

11 Google s Driverless Car (2009) Uses artificial technology intelligence and makes decisions on its own (if mistake is made it will alert driver) Artificial / Computer Vision / GPS / Google Maps / Various Sensors Test Driving: Ted by Sebastian Thrun: Artificial (2016-Spring)

12 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!: CogniToy s dinosaur connected to Watson: Artificial (2016-Spring)

13 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 Artificial (2016-Spring)

14 The Next 50 Years: Human-Level AI To achieve a true human-level intelligence, brain-like information processing is required Creative Uncertain Adaptive Inattentive Sociable Emotional Versatile Illogical = 5! 100 < 10? Artificial (2016-Spring)

15 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 obeying 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 Artificial (2016-Spring)

16 What is Artificial (AI)? Branch of computer science that is concerned with the automation of 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 Artificial (2016-Spring)

17 What is Artificial (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, selfadaptation, 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 Artificial (2016-Spring)

18 Research Areas and Approaches Artificial Research Application Paradigm Learning Algorithms Inference Mechanisms Knowledge Representation Intelligent System Architecture Intelligent Agents Information Retrieval Electronic Commerce Data Mining informatics Natural Language Proc. Expert Systems Rationalism (Logical) Empiricism (Statistical) Connectionism (Neural) Evolutionary (Genetic) logical (Molecular) Artificial (2016-Spring)

19 Paradigms for Artificial Symbolic AI Rule-Based Systems Connectionist AI Neural Networks Evolutionary AI Genetic Algorithms Molecular AI: DNA Computing Artificial (2016-Spring)

20 Paradigms for Computational Metaphor Symbolism Connectionism Dynamicism Symbol system Neural system Dynamical system Hyperinteractionism molecular 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 [Zhang, IEEE CIM, 2008] Graph theory, probabilistic logic Space/time Formal Spatial Temporal Spatiotemporal Artificial (2016-Spring)

21 Artificial 2015-Spring AI History and Highlights: Appendix intelligence Lab, SNU Artificial (2016-Spring)

22 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 [Stuart Russell's (Berkeley) course slides] 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 Artificial (2016-Spring)

23 [Stuart Russell's (Berkeley) course slides] 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! Artificial (2016-Spring)

24 [Stuart Russell's (Berkeley) course slides] 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? Artificial (2016-Spring)

25 [Stuart Russell's (Berkeley) course slides] 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 Artificial (2016-Spring)

26 [Xiao-Jun Zeng s (Univ. of Manchester) course slides] Brief history of AI - Golden years 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." Artificial (2016-Spring)

27 [Xiao-Jun Zeng s (Univ. of Manchester) course slides] Brief history of AI - The first AI winter The first AI winter : 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 Artificial (2016-Spring)

28 Brief history of AI - Boom Boom : 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 [Xiao-Jun Zeng s (Univ. of Manchester) course slides] 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 Artificial (2016-Spring)

29 Brief history of AI - the second AI winter the second AI winter 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] Artificial (2016-Spring)

30 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 [Xiao-Jun Zeng s (Univ. of Manchester) course slides] 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 Artificial (2016-Spring)

31 [Byoung-Tak Zhang s Doosan seminar slides] AI in Movies: 2001 a Space Odyssey 2001 a Space Odyssey (1968, Stanley Kubrick) HAL-9000, 공상과학영화속의인간수준인공지능비서 우주선 Discovery 의관제와승무원보호를담당 현재상황을인식하고추론, 미래를예측하여행동을수행 미래를예측하고이를바탕으로행동하는능력은인간수준인공지능의핵심적인자질 [Movie clip] [HAL 9000: AI system] Artificial (2016-Spring)

32 Star Trek (1973 ~ 2013) Lieutenant Commander Data One of main characters of Star Trek Artificial intelligence android with self-consciousness AI in Movies: Star Trek [Byoung-Tak Zhang s Doosan seminar slides] [Movie clip] Cold-minded Android [Data: AI android] Continuously learns how human acts Human-like Android Artificial (2016-Spring)

33 [Byoung-Tak Zhang s Doosan seminar slides] AI in Movies: Bicentennial Man Bicentennial Man (1999) Android robot Andrew who is purchased as a household robot Emphasize humanity of AI robot If a robot spends enough time around humans, can he learn to become one of them? Emotion, Creativity, Curiosity, Achievement Need, Love Artificial (2016-Spring)

34 AI in Movies: I, Robot [Byoung-Tak Zhang s Doosan seminar slides] 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 [Movie clip] Three laws of robotics (Isaac Asimov, 1942) 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. These rules might occur unexpected problems. A.I. with exceptional results need to be studied Artificial (2016-Spring)

35 AI in Movies: A.I. [Byoung-Tak Zhang s Doosan seminar slides] 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 Artificial (2016-Spring)

36 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 AI in Movies: Iron Man 3 [Byoung-Tak Zhang s Doosan seminar slides] Artificial (2016-Spring)

37 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] Artificial (2016-Spring)

38 AI in Movies: Her [Byoung-Tak Zhang s Doosan seminar slides] 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 Interact Cognition Recognition Consciousness Express Perception Self-aware Communication Learn Concept Understanding Reasoning Creative Artistic Musical Human AI System Artificial (2016-Spring)