1. Christoph F. Eick: COSC 6368 and ‘What is AI?” 1 COSC 6368 and “What is AI?” 1.Introduction to AI (today, and TH) What is AI? Sub-fields of AI Problems investigated by AI research 2.Course Information

2. Christoph F. Eick: COSC 6368 and ‘What is AI?” 2 Part1a: Definitions of AI “AI centers on the simulation of intelligence using computers” “AI develops programming paradigms, languages, tools, and environments for application areas for which conventional programming fails” – Symbolic programming (LISP) – Functional programming – Heuristic Programming –Logical Programming (PROLOG) –Rule-based Programming (Expert system shells) –Soft Computing (Belief network tools, fuzzy logic tool boxes,…) –Object-oriented programming (Smalltalk)

3. Christoph F. Eick: COSC 6368 and ‘What is AI?” 3 More Definitions of AI Rich/Knight: ”AI is the study of of how to make computers do things which, at the moment, people do better” Winston: “AI is the study of computations that make it possible to perceive, reason, and act. Turing Test: If an artificial intelligent system is not distinguishable from a human being, it is definitely intelligent.

4. Christoph F. Eick: COSC 6368 and ‘What is AI?” 4 Physical Symbol System Hypothesis “What the brain does can be thought of at some level as a kind of computation” Physical Symbol System Hypothesis (PSSH): A physical symbol system has the sufficient and necessary means for general, intelligent actions. Remarks PSSH: 1.Subjected to empirical validation 2.If false  AI is quite limited 3.Important for psychology and philosophy

5. Christoph F. Eick: COSC 6368 and ‘What is AI?” 5 Questions/Thoughts about AI What are the limitations of AI? Can computers only do what they are told? Can computers be creative? Can computers think? What problems cannot be solved by computers today? Computers show promise to control the current waste of energy and other natural resources. Computer can work in environment that are unsuitable for human beings. If computers control everything --- who controls the computers? If computers are intelligent what civil rights should be given to computers? If computers can perform most of our work; what should the human beings do? Only those things that can be represented in computers are important. It is fun to play with computers.

6. Christoph F. Eick: COSC 6368 and ‘What is AI?” 6 Topics Covered in COSC 6368 More general topics: –heuristic search and search algorithm in general –logical reasoning (FOPL as a language) –making sense out of data AI-specific Topics: –resolution / theorem proving –reasoning in uncertain environments and belief networks –machine learning and data mining –brief coverage of planning, evolutionary computing, knowledge-based systems and philosophical aspects of AI –Exposure to AI tools (belief networks, decision trees,…)

7. Christoph F. Eick: COSC 6368 and ‘What is AI?” 7 2009 Organization COSC 6368 1.Introduction AI and Course Information (1-2 classes) 2.Heuristic Search (4-5 classes) 3.Evolutionary Computing (2 classes) 4.FOPL, Logical Reasoning, Resolution, and PROLOG (3-4 classes) 5.Inductive Learning, Reinforcement Learning, Brief Introduction to Data Mining (4 classes) 6.Knowledge-based Systems and Expert Systems (1 class) 7.Planning (1-2 classes) 8.Ontologies and Philosophical Aspects of AI (1-2 classes) 9.Belief Networks and Reasoning in Uncertain Environments (3- 4 classes) 10.Other Activities: midterm exam (1 class), review (2 classes), homework/project-related discussions(1 class), possibly paper walk-through (1 class).

8. Christoph F. Eick: COSC 6368 and ‘What is AI?” 8 AI in General and What Is not Covered in COSC 6368 Robotics is a quite important sub-field of AI, but very few teach it in the graduate AI class. Natural language understanding probably will not be covered. Intelligent Agents and AI for the Internet could/should possibly be covered in a little more depth. Artificial intelligence programming is not covered. Techniques employed in systems that automate decision making in uncertain environments deserves more attention (e.g. fuzzy logic, rule-based programming languages and expert system shells, fuzzy controllers).

9. Christoph F. Eick: COSC 6368 and ‘What is AI?” 9 Positive Forces for AI Knowledge Discovery in Data and Data Mining (KDD) Intelligent Agents for WWW Robotics (Robot Soccer, Intelligent Driving, Robot Waiters, industrial robots, rovers, toy robots…) Creating of Knowledge Bases and Sharing of Knowledge (especially for Science and Engineering) Computer Chess and Computer Games in General --- AI for Entertainment

10. Christoph F. Eick: COSC 6368 and ‘What is AI?” 10 6368 Homepage http://www2.cs.uh.edu/~ceick/6368.html IJCAI 2009 Homepage http://ijcai-09.org/ http://ijcai-09.org/

11. Christoph F. Eick: COSC 6368 and ‘What is AI?” 11 Course Elements  21 Lectures 3 Exams (two midterms, one final exam) 4 Graded Assignments (review questions, exam style paper and pencil problems, a few more challenging problems that might require programming; problems that require using AI tools; searching for something and reporting) Un-graded Homeworks (solutions will usually discussed in class) 1 Paper Walk-Throughs (group activity) if class size <20 Discussion of assignments and home works We will try to use more demos and animations --- we have to see if this turns out to be useful

12. AI Intelligent Agents & Distributed AI Planning Learning & Knowledge Discovery Communicating, Perceiving and Acting Coping with Vague, Incomplete and Uncertain Knowledge Knowledge-based and Expert Systems Searching Intelligently Logical Reasoning & Theorem Proving Knowledge Representation AI Programming Part1b:

13. Christoph F. Eick: COSC 6368 and ‘What is AI?” Part1b: Examples of Problems Investigated by Different Subfields of AI 13

14. Christoph F. Eick: COSC 6368 and ‘What is AI?” 14 Knowledge Representation Problem: Can the above chess board be cover by 31 domino pieces that cover 2 fields? AI’s contribution: object-oriented and frame-based systems, ontology languages, logical knowledge representation frameworks, belief networks

15. Christoph F. Eick: COSC 6368 and ‘What is AI?” 15 Natural Language Understanding I saw the Golden Gate Bridge flying to San Francisco. I ate dinner with a friend. I ate dinner with a fork. John went to a restaurant. He ordered a steak. After an hour John left happily. I went to three dentists this morning.

16. Christoph F. Eick: COSC 6368 and ‘What is AI?” 16 Planning Objective: Construct a sequence of actions that will achieve a goal. Example: John want to buy a house

17. Christoph F. Eick: COSC 6368 and ‘What is AI?” 17 Heuristic Search Heuristo (greek): I find Copes with problems for which it is not feasible to look at all solutions Heuristics: rules a thumb (help you to explore the more promising solutions first), based on experience, frequently fuzzy Main ideas of heuristics: search space reduction, ordering solutions intelligently, simplifications of computations Example problems: puzzles, traveling salesman problem, …

18. Christoph F. Eick: COSC 6368 and ‘What is AI?” 18 Figure

19. Christoph F. Eick: COSC 6368 and ‘What is AI?” 19 Evolutionary Computing Evolutionary algorithms are global search techniques. They are built on Darwin’s theory of evolution by natural selection. Numerous potential solutions are encoded in structures, called chromosomes. During each iteration, the EA evaluates solutions adn generates offspring based on the fitness of each solution in the task. Substructures, or genes, of the solutions are then modified through genetic operators such as mutation or recombination. The idea: structures that led to good solutions in previous evaluations can be mutated or combined to form even better solutions.

20. Christoph F. Eick: COSC 6368 and ‘What is AI?” 20 Logical Reasoning Learn how to represents natural language statements in logic (AI as language) Automated theorem proving Foundation for PROLOG

21. Christoph F. Eick: COSC 6368 and ‘What is AI?” 21 Soft Computing Conventional Programming: Relies on two-valued logic Mostly uses a symbolic (non-numerical knowledge representation framework) Soft Computing (e.g. Fuzzy Logic, Belief Networks,..): Tolerance for uncertainty and imprecision Uses weights, probabilities, possibilities Strongly relies on numeric approximation and interpolation Remark: There seem to be two worlds in computer science; one views the world as consisting of numbers; the other views the world as consisting of symbols.

22. Christoph F. Eick: COSC 6368 and ‘What is AI?” 22 Learning agent receives feedback with respect to its actions (e.g. using a teacher) – Supervised Learning/Learning from Examples/Inductive Learning: feedback is received with respect to all possible actions of the agent – Reinforcement Learning: feedback is only received with respect to the taken action of the agent Unsupervised Learning: Learning without feedback Different Forms of Learning

23. Christoph F. Eick: COSC 6368 and ‘What is AI?” 23 Machine Learning Classification- Model Construction (1) Training Data Classification Algorithms IF rank = ‘professor’ OR years > 6 THEN tenured = ‘yes’ Classifier (Model)

24. Christoph F. Eick: COSC 6368 and ‘What is AI?” 24 Classification Process (2): Use the Model in Prediction Classifier Testing Data Unseen Data (Jeff, Professor, 4) Tenured?

25. Christoph F. Eick: COSC 6368 and ‘What is AI?” 25 Knowledge Discovery in Data [and Data Mining] (KDD) Let us find something interesting! Definition := “KDD is the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data” (Fayyad)

26. Christoph F. Eick: COSC 6368 and ‘What is AI?” 2. General Course Information Course Id: COSC 6368 Machine Learning Time: TU/TH 1-2:30 Instructor: Christoph F. Eick Classroom:232 PGH E-mail: ceick@aol.comceick@aol.com Homepage: http://www2.cs.uh.edu/~ceick/http://www2.cs.uh.edu/~ceick/

27. Christoph F. Eick: COSC 6368 and ‘What is AI?” Prerequisites Background Algorithms –basic data structures, complexity… Sound programming skills (no knowledge of LISP or PROLOG is requred) Ability to deal with “abstract mathematical concepts” Basic knowledge of logic would be helpful

28. Christoph F. Eick: COSC 6368 and ‘What is AI?” Textbook http://aima.cs.berkeley.edu/

29. Christoph F. Eick: COSC 6368 and ‘What is AI?” Grading 2 Exams60% 4 Assignment 40% NOTE: PLAGIARISM IS NOT TOLERATED. Remark: Weights are subject to change

30. Christoph F. Eick: COSC 6368 and ‘What is AI?” Tentative 2009 Teaching Plan (Subject To Change) WeekTopic Jan 20 Introduction / Search Jan 27 Search Feb. 3 Search/Evolutionary Computing (EC) Feb. 10 EC, Logical Reasoning (LR) Feb. 17 LR Feb. 24 LR/Learning from Examples(LFE) March 3 LFE/Reinforcement Learning March 10 Review,/Midterm Exam March 24 Leftovers/Knowledge-based Systems March 31 Ontologies/ Philosophical Foundations of AI April 7 Planning April 14 Reasoning in Uncertain Environments (RIE) April 21 RIE April 28 RIE/Review for Final Exam Remark: Topics in brown color may be skipped or replaced by something else

31. Christoph F. Eick: COSC 6368 and ‘What is AI?” Dates to Remember Dates to rememberEvents Last day before Spring Break; May 12 Exams March 17 /19No class (Spring Break)

32. Christoph F. Eick: COSC 6368 and ‘What is AI?” Exams  Will be open notes/textbook  Will get a review list before the exam  Exams will center (80% or more) on material that was covered in the lecture  Exam scores will be immediately converted into number grades  A few sample exams are available

33. Christoph F. Eick: COSC 6368 and ‘What is AI?” Other UH-CS Courses with Overlapping Contents COSC 6342: Machine Learning COSC 6342: Machine Learning Strong Overlap: Decision Trees, Bayesian Belief Networks, Learning from Examples in general Strong Overlap: Decision Trees, Bayesian Belief Networks, Learning from Examples in general Medium Overlap: Reinforcement Learning Medium Overlap: Reinforcement Learning COSC 6335: Data Mining COSC 6335: Data Mining Overlap: Decision trees, Learning from Examples in general Overlap: Decision trees, Learning from Examples in general Preprocessing/Exploratory DA, AdaBoost Preprocessing/Exploratory DA, AdaBoost COSC 6367: Evolutionary Computing Overlap: Search Overlap: Search We also will have 2 lectures on Evolutionary Computing We also will have 2 lectures on Evolutionary Computing