STRUCTURES AND STRATEGIES FOR STATE SPACE SEARCH 3 3.0Introduction 3.1Graph Theory 3.2Strategies for State Space Search 3.3Using the State Space to Represent.

Slides:



Advertisements
Similar presentations
CSC411Artificial Intelligence 1 Chapter 3 Structures and Strategies For Space State Search Contents Graph Theory Strategies for Space State Search Using.
Advertisements

Part2 AI as Representation and Search
CS 480 Lec 3 Sept 11, 09 Goals: Chapter 3 (uninformed search) project # 1 and # 2 Chapter 4 (heuristic search)
Structures and Strategies For Space State Search
Graphs Chapter 20 Data Structures and Problem Solving with C++: Walls and Mirrors, Carrano and Henry, © 2013.
Graph Search Methods Spring 2007 CSE, POSTECH. Graph Search Methods A vertex u is reachable from vertex v iff there is a path from v to u. A search method.
Lecture 3 Note: Some slides and/or pictures are adapted from Lecture slides / Books of Dr Zafar Alvi. Text Book - Aritificial Intelligence Illuminated.
Artificial Intelligence Chapter 14. Resolution in the Propositional Calculus Artificial Intelligence Chapter 14. Resolution in the Propositional Calculus.
CHAPTER 13 Graphs DATA ABSTRACTION AND PROBLEM SOLVING WITH C++ WALLS AND MIRRORS Third Edition Frank M. Carrano Janet J. Prichard Data Abstraction and.
HEURISTIC SEARCH ARTIFICIAL INTELLIGENCE 5th edition George F Luger
1 CALCULUS Even more graphing problems
Artificial Intelligence
Toy Problem: Missionaries and Cannibals
Cooperating Intelligent Systems Course review AIMA.
Structures and Strategies for State Space Search
Structures and Strategies for State Space Search
1 Heuristic Search 4 4.0Introduction 4.1An Algorithm for Heuristic Search 4.2Admissibility, Monotonicity, and Informedness 4.3Using Heuristics in Games.
Control and Implementation of State Space Search
1 Structures and Strategies for State Space Search 3 3.0Introduction 3.1Graph Theory 3.2Strategies for State Space Search 3.3Using the State Space to Represent.
Alyce Brady CS 510: Computer Algorithms Depth-First Graph Traversal Algorithm.
1 Tree Searching Strategies. 2 The procedure of solving many problems may be represented by trees. Therefore the solving of these problems becomes a tree.
1 Structures and Strategies for State Space Search 3 3.0Introduction 3.1Graph Theory 3.2Strategies for State Space Search 3.3Using the State Space to Represent.
Structures and Strategies For Space State Search
Artificial Intelligence Chapter 14 Resolution in the Propositional Calculus Artificial Intelligence Chapter 14 Resolution in the Propositional Calculus.
Automated Reasoning ARTIFICIAL INTELLIGENCE 6th edition George F Luger
HEURISTIC SEARCH. Luger: Artificial Intelligence, 5 th edition. © Pearson Education Limited, 2005 Portion of the state space for tic-tac-toe.
1 Heuristic Search 4 4.0Introduction 4.1An Algorithm for Heuristic Search 4.2Admissibility, Monotonicity, and Informedness 4.3Using Heuristics in Games.
1 Structures and Strategies for State Space Search 3 3.0Introduction 3.1Graph Theory 3.2Strategies for State Space Search 3.3Using the State Space to Represent.
Artificial Intelligence Course outline Introduction Problem solving Generic algorithms Knowledge Representation and Reasoning Expert Systems Uncertainty.
Strong Method Problem Solving.
Lecture 5 Note: Some slides and/or pictures are adapted from Lecture slides / Books of Dr Zafar Alvi. Text Book - Aritificial Intelligence Illuminated.
Formal Description of a Problem In AI, we will formally define a problem as –a space of all possible configurations where each configuration is called.
The Predicate Calculus
KU NLP Structures and Strategies for State Space Search Depth-First and Breadth-First Search q A search algorithm must determine the order in which.
Propositional Calculus Composed of symbols –P – some true statement P might represent something like “It is Monday” or “the car is red” And sentences –a.
Understanding Natural Language
Knowledge Representation CPTR 314. The need of a Good Representation  The representation that is used to represent a problem is very important  The.
Building Control Algorithms For State Space Search.
1 CS 385 Fall 2006 Chapter 3 Structures and Strategies for State Space Search.
Artificial Intelligence Tarik Booker. What we will cover… History Artificial Intelligence as Representation and Search Languages used in Artificial Intelligence.
CS 415 – A.I. Slide Set 5. Chapter 3 Structures and Strategies for State Space Search – Predicate Calculus: provides a means of describing objects and.
Structures and Strategies For Space State Search
George F Luger ARTIFICIAL INTELLIGENCE 5th edition Structures and Strategies for Complex Problem Solving HEURISTIC SEARCH Luger: Artificial Intelligence,
George F Luger ARTIFICIAL INTELLIGENCE 6th edition Structures and Strategies for Complex Problem Solving HEURISTIC SEARCH Luger: Artificial Intelligence,
Formal Description of a Problem In AI, we will formally define a problem as –a space of all possible configurations where each configuration is called.
KNOWLEDGE REPRESENTATION 6 6.0Issues in Knowledge Representation 6.1A Brief History of AI Representational Systems 6.2Conceptual Graphs: A Network Language.
Lecture 3: Uninformed Search
The man bites the dog man bites the dog bites the dog the dog dog Parse Tree NP A N the man bites the dog V N NP S VP A 1. Sentence  noun-phrase verb-phrase.
Data Abstraction and Problem Solving with JAVA Walls and Mirrors Frank M. Carrano and Janet J. Prichard © 2001 Addison Wesley Data Abstraction and Problem.
1 Solving problems by searching Chapter 3. Depth First Search Expand deepest unexpanded node The root is examined first; then the left child of the root;
George F Luger ARTIFICIAL INTELLIGENCE 5th edition Structures and Strategies for Complex Problem Solving Structures and Strategies For Space State Search.
George F Luger ARTIFICIAL INTELLIGENCE 5th edition Structures and Strategies for Complex Problem Solving HEURISTIC SEARCH Luger: Artificial Intelligence,
HEURISTIC SEARCH 4 4.0Introduction 4.1An Algorithm for Heuristic Search 4.2Admissibility, Monotonicity, and Informedness 4.3Using Heuristics in Games 4.4Complexity.
Splay Trees Data Structures & Problem Solving Using JAVA Second Edition Mark Allen Weiss Chapter 22 © 2002 Addison Wesley.
STRUCTURES AND STRATEGIES FOR STATE SPACE SEARCH 3 3.0Introduction 3.1Graph Theory 3.2Strategies for State Space Search 3.3Using the State Space to Represent.
Ch. 3 – Search Supplemental slides for CSE 327 Prof. Jeff Heflin.
Artificial Intelligence Midterm 고려대학교 컴퓨터학과 자연어처리 연구실 임 해 창.
CPSC 322, Lecture 5Slide 1 Uninformed Search Computer Science cpsc322, Lecture 5 (Textbook Chpt 3.5) Sept, 13, 2013.
George F Luger ARTIFICIAL INTELLIGENCE 5th edition Structures and Strategies for Complex Problem Solving STOCHASTIC METHODS Luger: Artificial Intelligence,
Spanning Trees Alyce Brady CS 510: Computer Algorithms.
Artificial Intelligence
AI Classnotes #5, John Shieh, 2012
Search Exercise Search Tree? Solution (Breadth First Search)?
Introduction: Some Representative Problems
CSE 421, University of Washington, Autumn 2006
Two – One Problem Legal Moves: Slide Rules: 1s’ move right Hop
Two – One Problem Legal Moves: Slide Rules: 1s’ move right Hop
CSE 421 Richard Anderson Autumn 2019, Lecture 3
Presentation transcript:

STRUCTURES AND STRATEGIES FOR STATE SPACE SEARCH 3 3.0Introduction 3.1Graph Theory 3.2Strategies for State Space Search 3.3Using the State Space to Represent Reasoning with the Predicate Calculus 3.4Epilogue and References 3.5Exercises Slide 3.1

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.2 Figure 3.14: Graph of Figure 3.13 at iteration 6 of breadth-first search. States on open and closed are highlighted.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.3 Function depth_first_search algorithm

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.4 A trace of depth_first_search on the graph of Figure 3.13

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.5 Figure 3.15: Breadth-first search of the 8-puzzle, showing order in which states were removed from open.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.6 Figure 3.16: Graph of Figure 3.13 at iteration 6 of depth-first search. States on open and closed are highlighted.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.7 Figure 3.17: Depth-first search of the 8-puzzle with a depth bound of 5.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.8 Figure 3.18: State space graph of a set of implications in the propositional calculus.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.9 Figure 3.19: And/or graph of the expression q Ÿ r  p.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.10

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.11 Figure 3.20: And/or graph of the expression q  r  p.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.12 Figure 3.21: And/or graph of a set of propositional calculus expressions.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.13 Figure 3.22: And/or graph of part of the state space for integrating a function, from Nilsson (1971).

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.14 The facts and rules of this example are given as English sentences followed by their predicate calculus equivalents:

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.15 Figure 3.23: The solution subgraph showing that fred is at the museum.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.16 Five rules for a simple subset of English grammar are:

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.17 Figure 3.24: And/or graph searched by the financial advisor.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.18 Figure 3.25:And/or graph for the grammar of Example Some of the nodes (np, art, etc.) have been written more than once to simplify drawing the graph.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.19 Figure 3.26: Parse tree for the sentence “The dog bites the man.” Note that this is a subtree of the graph of Figure 3.25.

A R T I F I C I A L I N T E L L I G E N C E: Structure and Strategies for Complex Problem Solving, 4th Edition George F. Luger © 2002 Addison Wesley Slide 3.20 Figure 3.27: A graph to be searched.