Artificial Intelligence. Dr. Onn Shehory Site:

Transcription

1 Artificial Intelligence Dr. Onn Shehory Site:

2 Outline Administrativa Course overview What is AI? Historical background The state of the art

3 Administrativa The course is based on lectures, lecture notes, and additional materials provided either electronically or in hard copy The recommended textbook is Artificial Intelligence a Modern Approach by Russell and Norvig There will be one final exam and no midterms Grading will be based on exam (at least 80%) and assignments (maximum 20%) There will be up to 4 assignments Late submission of assignments will be penalized for

4 Intelligent agents Problem solving Search Game playing Logical systems First-order logic Planning systems Learning Course Topics

5 What is AI? [The automation of] activities that we associate with human thinking, activities such as decision-making, problem solving, learning (Bellman 1978) The study of how to make computers do things at which, at the moment, people are better (Rich & Knight 1991) The study of mental faculties through the use of computational models (Charniak & McDermott 1985) The branch of computer science that is concerned with the automation of intelligent behavior (Luger & Stubblefield, 1993) So, views of AI fall into 4 categories: Thinking humanly Acting humanly Thinking rationally Acting rationally We vote for acting rationally (or similar)

6 Acting humanly: the Turing Test Turing (1950), Computing machinery and intelligence : Can machines think? Can machines behave intelligently? Operational test for intelligent behavior: the Imitation Game Predicted: by year 2000, a machine will have a 30% chance to fool a novice for 5 minutes Anticipated major arguments against AI Suggested major AI components: knowledge, reasoning, learning, language understanding Problems: not reproducible, not constructive, not amenable to mathematical analysis

7 Required computer capabilities To pass the test, a machine needs: Natural language processing Knowledge representation Automated reasoning Machine learning Turing test avoids physical interaction The Total Turing Test: includes video signal and passing objects To pass this test a machine will need: Computer vision Robotics

8 Thinking humanly: Cognitive Science For making machines think like humans, we need to understand how humans think: Introspect ourselves to catch thoughts Perform psychological experiments In the 60 s: information-processing psychology replaced the orthodoxy of behaviorism Requires scientific theories of internal brain activities: What level of abstraction? Knowledge or circuits? How to validate? Top-down: predicting and testing behavior of human subjects Bottom-up: direct identification from neurological data Note: both approaches (Cognitive Science and Neuroscience) are distinct from AI

9 General Problem Solver (GPS) Newell, Shaw and Simon (1961) Could solve problems such as Missioners & cannibals Irish beer Towers of Hanoi The main concern: not the right solution, but comparing reasoning traces to human reasoning Wang (1960) concentrated on getting the right solution, regardless of the human way

10 Thinking rationally: laws of thought Normative (prescriptive) rather than descriptive It all begun in Greece: Aristotle right thinking irrefutable reasoning, syllogisms Example: Socrates is a man; all men are mortal; therefore Socrates is mortal Other Greek schools suggested other forms of logic: Notations and rules of derivation for thoughts These lead, through Math and philosophy, to AI Problems: Not all intelligent behavior is mediated by logical deliberation What s the purpose of thinking? What thoughts should we have?

11 Logic Formal logic: Late 1800 s through early 1900 s Provided a precise notation for statements about objects in the world and relations In 1965, a program that can solve any problem described in logical notation* * Obstacle to the logicist approach: Not easy to convert informal to formal Practically, solution path is too complex

12 Acting rationally Rational behavior: doing the right thing The right thing is the one that is expected to maximize goal achievement, given the available information Correct inference is important, but not enough: Sometimes there is no correct thing, but action is necessary Some rational action does not involve inference, e.g., reflex Yet, thinking should be in service of rational action Note: doing always the right thing is not possible in complex environments

13 Rational agents An agent: perceives and acts (rationally) This course is about designing (intelligent activity of) such agents Abstractly, all we need is a function from percept histories to actions: f: P* A Rational: for any given class of environments and tasks, we seek the agent with the best performance Bounded rationality: design the best program given the limited computational resources

14 Historical background Philosophy: Logic, reasoning methods The mind as a physical system Foundations of learning, language, rationality Mathematics: Formal representation and proof algorithms Computation, (un)decidability, (in)tractability, probability Psychology: Phenomena of perception and motor control Experimental techniques (psychophysics, etc.) Linguistics: knowledge representation, grammar Neuroscience: physical substrate for mental activity Control theory: Simple optimal agent designs stability

15 AI history in brief 1943 McCulloch & Pitts: Boolean circuit of brain 1950 Turing s Computing machinery and intelligence The look, Ma, no hands! era 1950s Early AI programs: Samuel s checkers program, Newell & Simon s Logic Theorist, GPS, Gelernter s Geometry Engine 1956 Dartmouth meeting: McCarthy s Artificial Intelligence 1958 McCarthy: Lisp, time sharing, DEC, Advice Taker 1965 Robinson s complete algorithm for logical reasoning 1965 Weizenbaum s ELIZA AI discovers computational complexity Early development of knowledge-based systems (Dendral) Expert systems industry booms (Mycin) AI winter Neural networks comeback Increase: probabilistic and decision-theoretic methods, mainstream New: Alife, GA, distributed AI 1997 Deep Blue wins against Kasparov 2011 Watson wins Jeopardy 2050 Robotic soccer team wins world cup?

16 State of the art Which can be done today? Play a decent game of table tennis Drive along a curving mountain gravel road Drive in the center of Cairo Play a decent game of bridge Discover and prove a new mathematical theorem Write an intentionally funny story Give a competent legal advice in a specialized area of law Translate spoken English into Spoken Swedish in real time Compose (and play) a high-quality soundtrack for a movie