Course Notes [PowerPoint 2003 format] and Topics:

• June 1: Introduction to AI
• June 3: Knowledge Representations and Uncertainty Handling
• June 8: Ontologies
• June 10: Agents
• June 15: Bayesian Probabilities
  liver diagnosis example mammogram interpretation example travel utility function example sensors example
• June 17: Hidden Markov Models
  BioInformatics HMM example Spacecraft Monitoring HMM example Terrorist Identification HMM example Customer Relations HMM example
• June 24: Neural Networks
  2 image applications 2 prediction applications ALVINN.jpg Traveling salesman problem solution Football play prediction
• June 29: Speech Recognition
• July 1: Robotics
• July 6: Homeland Security
• July 13: Diagnosis and Interpretation
• July 20: no notes, student presentations
• July 22: AI in the Future and AI Ethics

Reading List:

A comment before the actual list because you will find A LOT of stuff here. You do not need to read everything listed. I want you to read enough so you are conversant in the topic. So you might start with the first item and read it until you feel you have seen enough, and then move onto the next item. If you are unsure whether to read something, you can contact me. If you want to know more about a topic, continue down the list. Usually the first item in the list is the most important.

• Readings for Monday, June 1:
  • John McCarthy intro to AI
  • A brief history of AI
  • Minds, brains, and programs by Searle
  • Chat with A.L.I.C.E.

• Readings for Wednesday, June 3:
  • Chapter 1 of Computational Intelligence by David Poole
  • Various introductory topics including search, representations, and dealing with uncertainty (scroll to the bottom of this page)
  • Tutorial on fuzzy logic -- If this link does not work, try this one instead.
  • Introduction to Bayesian Probabilities and Networks
    Additional items:
    
  • Some slides on knowledge representation
  • Some more slides on knowledge representations

• Readings for Monday, June 8:
  • What Are Ontologies?
  • Introduction to CYCL
  • OWL Ontology

    Additional items:

  • For more on OWL, see OWL Specifics
  • For more on CYC, visit the Cycorp web site which has a ton of papers available
  • Other ontologies are also available: Ontolingua, OIL, KM, and see Wikipedia's entry on Ontologies.
  • Are these ontologies? figures excerpted from http://www.jfsowa.com/pubs/semnet.htm and other sources
  • Military Ontology power point presentation from http://citeseer.ist.psu.edu/455877.html
  • Calendar Agent ontology from http://www.kingtiny.net/publications/IEEE-RCal.pdf

• Readings for Wednesday, June 10:
  • Chapter 2 of Russell and Norvig's Artificial Intelligence: A Modern Approach text, this chapter is on Intelligent Agents
  • A Taxonomy for Autonomous Agents
  • The Semantic Web by Berners-Less, Hendler and Lassila

    Additional Items:

  • The Retsina architecture
  • The Semantic Web: An Introduction
  • The Semantic Web in Action an update on semantic web progress as of 2007
  • METEOR-S Research Site which has links to a number of publications about the METEOR-S web service architecture to support the semantic web

• Readings for Monday, June 15:
  • A nice introduction is given in Bayesian Networks Without Tears by Charniak (AI Magazine, 1991)

    If you need more details, here are some additional resources:

  • this web site for an introduction to Bayesian reasoning
  • Bayesian Belief Nets
  • An Introduction to Bayesian Networks and Their Contemporary Applications

• Readings for Wednesday, June 17:
  • A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition -- read the first 10 pages, you can stop once you have reached the end of section III (you will read more of this later in the term)
  • The Ice Cream Cone Example -- stored as an excel spreadsheet

• Readings for Wednesday, June 24:
  Select one or more of the following readings until you feel you have a basic understanding of perceptrons, feedforward/backprop nets, and an idea of some of the other forms of neural networks (e.g., self organizing maps).
  • Genevieve Orr's Neural Networks course notes -- in particular, read Lecture 1, 2, 4 (up through Backprop) and the material on self orgazning Kohonon maps
  • Neural Networks tutorial from StatSoft inc up through multilayered perceptrons and the material on SOFM networks
  • IBM's Introduction to Neural Networks
  • Neural Networks in Plain English

• Readings for Monday, June 29
  • A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition -- read the article from page 19 (the start of section VI) to the end
  • Speech Recognition Using Neural Networks

    You may also want to read or skim through the following:
    

  • A Brief History of Speech Recognition
  • Hearsay-II

  • The CMU Speech site with a link to Sphinx if you are interested in downloading and playing with one of the available Sphinx platforms

• Readings for Wednesday, July 1
  • Skim through this article on Stanley, Stanford's autonomous vehicle which won the 2005 DARPA Grand Challenge
  • Intelligence Without Representation by Rodney Brooks
    
  • You might also want to explore the Cog site

• Readings for Monday, July 6
  • Read this introduction about AI and Homeland Security Dark Web

  • You can find additional articles (many in popular publications rather than technical journals) at AAAI.org under these topics: Public Health and Welfare Law Enforcement and Public Safety Hazards and Disasters

• Readings for Monday, July 13
  Read any of the following, but start off with
  • A technical report that I co-authored around 1991 about the Evolution vs Creationism case, implemented using Peirce. Warning: this version does not contain any references. I can add those later if needed.
  • A brief introduction to AI in Medicine
  • The MYCIN experience has been written up as a book by Edward H. Shortliffe called Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. You might want to take a look at some of the early chapters that discuss the rule-based approach. Or not.
  • Models of Scientific Explanation by Thagard and Litt
  • Fundamentals of Model-based Diagnosis by de Kleer and Kurien
  • A list of medical systems in routine use

• No readings for Monday, July 20, student presentations

• Readings for Wednesday, July 22
  • Read either the full version of the Investigation of the Therac-25 Accidents or the short reprint
    In addition, you might want to read some of the following:
  • Infinite Memory and Bandwidth: Implications for Artificial Intelligence
  • Ethical Issues in Advanced Artificial Intelligence
  • Why the Future Doesn't Need Us
  • The Age of Intelligent Machines

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