'8 queens' presentation slideshows

Goals of Course

These notes are intended for use by students in CS1501 at the University of Pittsburgh and no one else These notes are provided free of charge and may not be sold in any shape or form

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Chapter 04

Chapter 04. Artificial Intelligence. Informed search algorithms and Beyond Classical Search. Beyond Classical Search. Local search algorithms/ Iterative Improvement Algorithms and Optimization Problems Hill-Climbing Search Simulated Annealing Genetic Algorithms. Beyond Classical Search.

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8-Queens: Search Formulation #1

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Problem Solving

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Backtracking and Game Trees

Backtracking and Game Trees. 15-211: Fundamental Data Structures and Algorithms. Margaret Reid-Miller 5 April 2005. Announcements. HW5 now available! May do in groups of two. Review in recitation No fancy data structures except trie! Due Monday 11:59 pm. A. X O X O X O X O O. B. C.

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Search

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Prolog - Conclusions

Prolog - Conclusions. Outline. Numeric computation in Prolog Problem space search Knapsack 8-queens Farewell to Prolog. Unevaluated Terms. Prolog operators allow terms to be written more concisely, but are not evaluated These are all the same Prolog term:

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CS B551: Elements of Artificial Intelligence

CS B551: Elements of Artificial Intelligence. Instructor: Kris Hauser http://cs.indiana.edu/~hauserk. Recap. http://www.cs.indiana.edu/classes/b551 Brief history and philosophy of AI What is intelligence? Can a machine act/think intelligently? Turing machine, Chinese room. Agenda.

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Constraint Satisfaction Problems

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CSE 143 Lecture 18

CSE 143 Lecture 18. Recursive Backtracking Based on slides by Marty Stepp & Ethan Apter. Exercise. Write a method permute that accepts a string as a parameter and outputs all possible rearrangements of the letters in that string. The arrangements may be output in any order.

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Problem Solving and Search in AI Part I

Problem Solving and Search in AI Part I. Search and Intelligence. Search is one of the most powerful approaches to problem solving in AI Search is a universal problem solving mechanism Systematically explores the alternatives Finds the sequence of steps towards a solution

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Randomized Algorithms

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Implementing Search

Implementing Search. Lecture 2-2 January 14 th /19 th , 1999 CS250. 8-Puzzle. States? Operators? Goal test? Path cost?. 8-Queens. Place 8 queens on a chess board, with no one attacking any other Goal test? Path cost? States Operators?. Cryptarithmetic.

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SOLVING PROBLEMS BY SEARCHING

SOLVING PROBLEMS BY SEARCHING. Feng Zhiyong Tianjin University Fall 2008. Problem-solving Agents. Formulating Problems. Well-defined problems and solutions. datatype PROBLEM components: INITIAL-STATE, OPERATORS, GOAL-TEST, PATH-COST-FUNCTION Measuring problem-solving performance

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PROLOG

PROLOG. 8 QUEENS PROBLEM. 8 QUEENS. Place 8 queens on an 8 X 8 chessboard so that: Queens do not attack each other. 8 QUEENS. Solution will be programmed as a unary predicate solution(Position)

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CSE 143 Lecture 19

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Backtracking

Backtracking. COP 3502. Backtracking. Junction. Backtracking is a technique used to solve problems with a large search space, by systematically trying and eliminating possibilities. A standard example of backtracking would be going through a maze.

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CSE 143 Lecture 17

CSE 143 Lecture 17. Recursive Backtracking slides created by Marty Stepp http://www.cs.washington.edu/143/. Exercise.

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Program Development by Stepwise Refinement

Program Development by Stepwise Refinement. Niklaus Wirth. Motivation. Programming is usually taught via examples Examples normally demonstrate what a computer can do Examples are not normally chosen by their suitability for a technique

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The "8 Queens" problem

The "8 Queens" problem. Consider the problem of trying to place 8 queens on a chess board such that no queen can attack another queen. What are the "choices"? How do we "make" or "un-make" a choice? How do we know when to stop?. Naive algorithm. for (each square on board):

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