• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Class overview, intro to AI - Belief-optimal Reasoning for Cyber ...
 

Class overview, intro to AI - Belief-optimal Reasoning for Cyber ...

on

  • 230 views

 

Statistics

Views

Total Views
230
Views on SlideShare
230
Embed Views
0

Actions

Likes
0
Downloads
2
Comments
0

0 Embeds 0

No embeds

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    Class overview, intro to AI - Belief-optimal Reasoning for Cyber ... Class overview, intro to AI - Belief-optimal Reasoning for Cyber ... Presentation Transcript

    • CS B351: Intro to Artificial Intelligence and Computer Simulation
      Instructor: Kris Hauser
      http://cs.indiana.edu/~hauserk
      1
    • Basics
      Class web site
      http://cs.indiana.edu/courses/b351
      Textbook
      S. Russell and P. Norvig
      Artificial Intelligence: a Modern Approach
      2nd edition or 3rd edition
      2
    • Basics
      Instructor
      Kris Hauser (hauserk@indiana.edu)
      AIs
      Mark Wilson (mw54@indiana.edu)
      3
    • Office Hours
      Kris Hauser
      M,Th 11-12 in Info W 300
      TAs
      W 1-3 in Lindley 406
      4
    • Agenda
      Intro to AI
      Overview of class policies
      5
    • Intro to AI
      6
    • What is AI?
      AI is the reproduction of human reasoning and intelligent behavior by computational methods
      7
    • What is AI?
      AI is an attempt of reproduction of human reasoning and intelligent behavior by computational methods
      8
    • What is AI?
      Discipline that systematizes and automates reasoning processes to create machines that:
      9
    • 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
      10
    • 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?
      11
    • 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?
      12
    • What is Intelligence?
      “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 (1598-1650)
      13
    • What is Intelligence?
      Turing Test (c. 1950)
      14
    • An Application of the Turing Test
      CAPTCHA: Completely Automatic Public Turing tests to tell Computers and Humans Apart
      15
    • Chinese Room (John Searle)
      16
    • Can Machines Act/Think Intelligently?
      • Yes, if intelligence is narrowly defined as information processingAI 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
    • Some Achievements
      • 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
      18
    • Can Machines Act/Think Intelligently?
      • Yes, if intelligence is narrowly defined as information processingAI 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
    • 20
    • Big Open Questions
      • 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)
      21
    • 22
      • 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
    • Main Areas 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
      23
      Agent
      Perception
      Robotics
      Reasoning
      Search
      Learning
      Knowledgerep.
      Constraintsatisfaction
      Planning
      Naturallanguage
      ...
      Expert
      Systems
    • Bits of History
      • 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
      24
    • Syllabus
      Introduction to AI
      Philosophy, history, agent frameworks
      Search
      Uninformed search, heuristic search, heuristics
      Search applications (and variants)
      Constraint satisfaction, planning, game playing, motion planning
      Reasoning under uncertainty
      Probability, planning under uncertainty, Bayesian networks, probabilistic inference, dynamic modeling
      Intro to machine learning
      Neural nets, decision tree learning, support vector machines, etc.
      25
    • 26
      Game theory
      Biologically-inspired computing
      Computer Vision
      E626
      B553
      I486
      B657
      B351
      Knowledge representation and learning
      B551
      B552
      S626
      S675
      Robotics
      B335
      I400
      Natural Language Processing
      Topics in AI
      B651
      B659
      Q360
      Q570
    • Careers in AI
      ‘Pure’ AI
      Academia, industry labs
      Applied AI
      Almost any area of CS!
      NLP, vision, robotics
      Economics
      Cognitive Science
      27
    • AI References
      Conferences
      IJCAI, ECAI, AAAI, NIPS
      Journals
      AI, Comp. I, IEEE Trans. Pattern Anal. Mach. Intel., IEEE Int. Sys., Journal of AIR
      Societies
      AAAI, SIGART, AISB
      AI Magazine (Editor: IU’s David Leake)
      28
    • Class Policies
      29
    • Prerequisites
      C211
      I recommend:
      Two semesters programming
      Basic knowledge of data structures
      Basic knowledge of algorithmic complexity
      30
    • Programming Assignments
      Projects will be written in Python
      Great for scripting
      Peter Norvig, Director of Research at Google, and textbook author
      Easy to learn
      2 weeks for each assignment
      31
    • Grading
      50% Homework
      6 assignments - lowest score will be dropped
      30% Final
      20% Midterm
      32
    • Homework Policy
      Due at end of class on due date
      Typically Tuesdays
      Extensions only granted in rare cases
      Require advance notice except emergencies
      33
    • Enrollment
      Add/drop deadline
      No penalty: Sept 3
      Late drop/add: Oct 27
      Waitlist deadline: Sept 4
      34
    • Takeaways
      AI has many interpretations
      Act vs. think, human-like vs. rational
      Concept has evolved
      ‘I’ has many interpretations
      Turing test
      Chinese room
      AI success stories from each perspective
      35
    • Homework
      Register
      Textbook
      Survey
      http://cs.indiana.edu/classes/b351
      Readings: R&N Ch. 1, 2, 26
      36