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  • Vilnius University

    Faculty of Mathematics and Informatics

    Vytautas yras

    ARTIFICIAL INTELLIGENCE

    http://www.mif.vu.lt/~cyras/AI/ai-cyras.pdf

    Vilnius

    2017

    http://www.mif.vu.lt/~cyras/AI/ai-cyras.pdf

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    Artificial Intelligence, 2017-10-29

    Table of Contents

    1. Introduction ........................................................................................................................ 5

    1.1. The Subject Matter of Artificial Intelligence .............................................................. 5

    1.2. The Towers of Hanoi .................................................................................................. 7

    1.3. Dynamic Nature of Artificial Intelligence ................................................................ 10

    1.4. Methods of Problem Solving .................................................................................... 10

    2. Artificial Intelligence System as a Production System .................................................. 12

    2.1. Testing ....................................................................................................................... 16

    3. Control with Backtracking and Procedure BACKTRACK ......................................... 17

    3.1. An Example of the DEADEND Predicate ................................................................ 18

    4. The 8-queens Puzzle ......................................................................................................... 19

    5. Heuristic ............................................................................................................................ 22

    5.1. Heuristic Search in N-queens Problem ..................................................................... 22

    5.2. Knights Move Heuristic in the N-queens Problem .................................................. 25

    6. BACKTRACK1 a Cycle-avoiding Algorithm ............................................................. 31

    7. Depth-first Search in a Labyrinth ................................................................................... 32

    7.1. Testing Depth-first Search in a Labyrinth ................................................................. 35

    8. Breadth-first Search in a Labyrinth ............................................................................... 37

    8.1. Testing Breadth-first Search in a Labyrinth .............................................................. 41

    9. Breadth-first Search in a Graph ..................................................................................... 43

    10. Shortest Path Problem in a Graph with Edge Weights ................................................ 46

    11. Depth-first Search in a Graph with no Weights ............................................................ 49

    12. The Prefix, Infix and Postfix order of Tree Traversal .................................................. 51

    13. GRAPHSEARCH Algorithm .......................................................................................... 56

    14. Differences between BACKTRACK1 and GRAPHSEARCH-DEPTH-FIRST ......... 57

    14.1. Searching in a Graph ................................................................................................. 57

    14.2. Multiple Cycles in a Labyrinth ................................................................................. 58

    14.3. A Counterexample to BACKTRACK1 Perform Better ............................................ 60

    15. Hill-climbing Strategy ...................................................................................................... 62

    16. Manhattan Distance ......................................................................................................... 65

    17. A* Search Algorithm ........................................................................................................ 67

    17.1. Manhattan Distance in the Tile World ...................................................................... 67

    17.2. An Example from Russell & Norvig 2003 ................................................................ 70

    18. Forward Chaining and Backward Chaining ................................................................. 73

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    Artificial Intelligence, 2017-10-29

    18.1. Forward Chaining...................................................................................................... 73

    18.2. Backward Chaining ................................................................................................... 74

    18.3. Program Synthesis ..................................................................................................... 75

    18.4. Redundant Rules in Forward Chaining ..................................................................... 77

    18.5. Redundant Rules in Backward Chaining .................................................................. 78

    18.6. Complexity of Forward Chaining ............................................................................. 78

    18.7. Testing Forward Chaining ......................................................................................... 78

    18.8. Testing Backward Chaining ...................................................................................... 80

    19. Resolution .......................................................................................................................... 83

    19.1. Inference Example .................................................................................................... 85

    19.2. Example with Three Rules ........................................................................................ 87

    19.3. Using Resolution to Prove Theorem ......................................................................... 90

    20. Expert Systems .................................................................................................................. 91

    21. Internet Shopping ............................................................................................................. 94

    22. The Turing Test .............................................................................................................. 100

    23. Intension, Extension and Ontology ............................................................................... 101

    23.1. Signs ........................................................................................................................ 102

    23.2. What is a Conceptualization? .................................................................................. 103

    23.3. What is a Proper Formal, Explicit Specification? ................................................... 107

    23.4. Distinct Models of a Specification .......................................................................... 112

    24. Examination Questions .................................................................................................. 115

    25. References ........................................................................................................................ 116

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    Artificial Intelligence, 2017-10-29

    Preface

    This course-book views artificial intelligence (AI) from the standpoint of programming.

    Fundamental concepts of classical AI are presented: problem solving by search, solver, planner,

    etc. A purpose is to understanding the spirit of a discipline of artificial intelligence.

    The course-book is available at http://www.mif.vu.lt/~cyras/AI/ai-cyras.pdf and presents

    primarily figures and text excerpts which are comprised in the broader Lithuanian edition1.

    The following themes are presented:

    History of artificial intelligence

    Philosophical questions

    The Turing test

    A system of artificial intelligence according to Nils Nilsson: 1) a global data base, 2) a set of production rules, and 3) a control system

    Examples: the 8 queens puzzle, the knights tour, path search in a labyrinth

    Problem spaces

    Backtracking

    Depth-first search and breadth-first search, Dijkstras algorithm, A*

    The role of heuristics

    Forward chaining and backward chaining

    Knowledge-based reasoning, deduction, resolution technique

    Hill climbing

    Elements of expert systems architecture: facts, rules, and an inference engine

    Knowledge representation

    Structured representation, frames and objects

    Semantic networks

    Artificial intelligence and law

    Extensional relational structure and what is an ontology

    Acknowledgements. Sincere thanks to students who contributed to this course-book.

    Edgaras Abromaitis work was essential in shaping the text and producing the figures.

    1 V. yras. Intelektualios sistemos. e-Book. ISBN 978-9955-33-561-0.

    .

    http://www.mif.vu.lt/~cyras/AI/ai-cyras.pdfhttp://www.mif.vu.lt/~cyras/AI/konspektas-intelektualios-sistemos.pdf

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    Artificial Intelligence, 2017-10-29

    1. Introduction

    Artificial intelligence is defined as the science of designing computer systems to perform tasks

    that would normally require human intelligence (Sowa 2000, p. XI). The term artificial

    intelligence was coined more than 50 years ago. This term was coined at the Dartmouth

    conference (1956), USA.

    1.1. The Subject Matter of Artificial Intelligence

    The subject matter of AI also shows the place of AI within the discipli

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