CS B351: I NTRO TO A RTIFICIAL I NTELLIGENCE AND C OMPUTER S IMULATION Instructor: Kris Hauser 1

B ASICS Class web site Textbook S. Russell and P. Norvig Artificial Intelligence: a Modern Approach 3 rd edition 2

B ASICS Instructor Kris Hauser AIs Dan Coroian 3

O FFICE H OURS Kris Hauser M 2-3,Th 2-3 in Info E 257 (connector building) Dan Coroian TBA 4

A GENDA Intro to AI Overview of class policies 5

W HAT IS AI? AI is the reproduction of human reasoning and intelligent behavior by computational methods 6

W HAT IS AI? AI is an attempt of reproduction of human reasoning and intelligent behavior by computational methods 7

W HAT IS AI? Discipline that systematizes and automates reasoning processes to create machines that: 8 Think like humans Think rationally Act like humans Act rationally

The goal of AI is: to build machines that operate in the same way that humans think How do humans think? Build machines according to theory, test how behavior matches mind’s behavior Cognitive Science Manipulation of symbolic knowledge How does hardware affect reasoning? Discrete machines, analog minds 9 Think like humans Think rationally Act like humans Act rationally

The goal of AI is: to build machines that perform tasks that seem to require intelligence when performed by humans Take a task at which people are better, e.g.: Prove a theorem Play chess Plan a surgical operation Diagnose a disease Navigate in a building and build a computer system that does it automatically But do we want to duplicate human imperfections? 10 Think like humans Think rationally Act like humans Act rationally

The goal of AI is: to build machines that make the “best” decisions given current knowledge and resources “Best” depending on some utility function Influences from economics, control theory How do self-consciousness, hopes, fears, compulsions, etc. impact intelligence? Where do utilities come from? 11 Think like humans Think rationally Act like humans Act rationally

W HAT IS I NTELLIGENCE ? “If there were machines which bore a resemblance to our bodies and imitated our actions as closely as possible for all practical purposes, we should still have two very certain means of recognizing that they were not real men. The first is that they could never use words, or put together signs, as we do in order to declare our thoughts to others… Secondly, even though some machines might do some things as well as we do them, or perhaps even better, they would inevitably fail in others, which would reveal that they are acting not from understanding, …” Discourse on the Method, by Descartes ( ) 12

W HAT IS I NTELLIGENCE ? Turing Test (c. 1950) 13

W HAT IS INTELLIGENCE ?

A N A PPLICATION OF THE T URING T EST CAPTCHA: Completely Automatic Public Turing tests to tell Computers and Humans Apart 15

C HINESE R OOM (J OHN S EARLE ) 16

C AN M ACHINES A CT /T HINK I NTELLIGENTLY ?  Yes, if intelligence is narrowly defined as information processing AI has made impressive achievements showing that tasks initially assumed to require intelligence can be automated Each success of AI seems to push further the limits of what we consider “intelligence” 17

S OME A CHIEVEMENTS  Computers have won over world champions in several games, including Checkers, Othello, and Chess, but still do not do well in Go  AI techniques are used in many systems: formal calculus, video games, route planning, logistics planning, pharmaceutical drug design, medical diagnosis, hardware and software trouble- shooting, speech recognition, traffic monitoring, facial recognition, medical image analysis, part inspection, etc...  DARPA Grand Challenge: robotic car autonomously traversed 132 miles of desert  IBM’s Watson competes with Jeopardy champs  Some industries (automobile, electronics) are highly robotized, while other robots perform brain and heart surgery, are rolling on Mars, fly autonomously, …, but home robots still remain a thing of the future 18

C AN M ACHINES A CT /T HINK I NTELLIGENTLY ?  Yes, if intelligence is narrowly defined as information processing AI has made impressive achievements showing that tasks initially assumed to require intelligence can be automated  Maybe yes, maybe not, if intelligence cannot be separated from consciousness  Is the machine experiencing thought?  Strong vs. Weak AI 19

B IG O PEN Q UESTIONS  Is intelligent behavior just information processing? (Physical symbol system hypothesis)  If so, can the human brain solve problems that are inherently intractable for computers? Will a general theory of intelligence emerge from neuroscience?  In a human being, where is the interface between “intelligence” and the rest of “human nature” Self-consciousness, emotions, compulsions  What is the role of the body? (Mind-body problem) 20

21  AI contributes to building an information processing model of human beings, just as Biochemistry contributes to building a model of human beings based on bio-molecular interactions  Both try to explain how a human being operates  Both also explore ways to avoid human imperfections (in Biochemistry, by engineering new proteins and drug molecules; in AI, by designing rational reasoning methods)  Both try to produce new useful technologies  Neither explains (yet?) the true meaning of being human

M AIN A REAS OF AI  Knowledge representation (including formal logic)  Search, especially heuristic search (puzzles, games)  Planning  Reasoning under uncertainty, including probabilistic reasoning  Learning  Robotics and perception  Natural language processing 22 Search Knowledge rep. Planning Reasoning Learning Agent Robotics Perception Natural language... Expert Systems Constraint satisfaction

B ITS OF H ISTORY  1956: The name “Artificial Intelligence” is coined  60’s: Search and games, formal logic and theorem proving  70’s: Robotics, perception, knowledge representation, expert systems  80’s: More expert systems, AI becomes an industry  90’s: Rational agents, probabilistic reasoning, machine learning  00’s: Systems integrating many AI methods, machine learning, natural language processing, reasoning under uncertainty, robotics again 23

AI R EFERENCES Conferences IJCAI, ECAI, AAAI, NIPS Journals AI, Comp. I, IEEE Trans. Pattern Anal. Mach. Intel., IEEE Int. Sys., JAIR Societies AAAI, SIGART, AISB AI Magazine (Editor: IU’s David Leake) 24

C AREERS IN AI ‘Pure’ AI Academia, industry labs Applied AI Almost any area of CS! NLP, vision, robotics Economics Cognitive Science 25

S YLLABUS Introduction to AI Philosophy, history, agent frameworks Search Uninformed search, heuristic search, heuristics, game playing Reasoning under uncertainty Probability, planning under uncertainty, Bayesian networks, probabilistic inference, temporal sequences Machine learning Neural nets, decision tree learning, support vector machines, etc. Applications Constraint satisfaction, motion planning, computer vision 26

C LASS P OLICIES 27

P REREQUISITES C211 I recommend: Two semesters programming Basic knowledge of data structures Basic knowledge of algorithmic complexity 28

P ROGRAMMING A SSIGNMENTS Projects will be written in Python Easy to learn 2 weeks for each assignment See Resources tab on class webpage for helpful links 29

G RADING 50% Homework 6 assignments, lowest score will be dropped 30% Final 15% Midterm 5% Participation 30

H OMEWORK P OLICY Due at end of class on due date Typically Thursdays No “slip days” Extensions only granted in rare cases Require advance notice except emergencies 31

F INAL P ROJECT Encouraged if you are intending to do research or coursework in AI, pursue higher degree Individual or small groups (up to 3) Counts as three homework assignments Content Software, new research, or technical report Mid-semester project proposal End-of-year report and in-class presentation

T AKEAWAYS AI has many interpretations Act vs. think, human-like vs. rational Concept has evolved “Intelligence” has many interpretations Turing test Chinese room AI success stories from each perspective 33

H OMEWORK Register Textbook Readings: R&N Ch. 1, 26 (introduction and historical perspectives) R&N