'Uninformed search strategies' presentation slideshows

CS 541: Artificial Intelligence

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Problem Solving

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Chapter 3 Solving problems by searching

Chapter 3 Solving problems by searching. Search. We will consider the problem of designing goal-based agents in observable , deterministic , discrete , known environments T he solution is a fixed sequence of actions

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An Introduction to Artificial Intelligence

An Introduction to Artificial Intelligence. Lecture 3: Solving Problems by Sorting Ramin Halavati (halavati@ce.sharif.edu). In which we look at how an agent can decide what to do by systematically considering the outcomes of various sequences of actions that it might take. Outline.

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Solving problems by searching

Solving problems by searching. Chapter 3. Outline. Problem-solving agents Problem types Problem formulation Example problems Basic search algorithms. Problem-solving agents. Example: Romania. On holiday in Romania; currently in Arad. Flight leaves tomorrow from Bucharest

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Administrative

Administrative. Project due Tuesday: Email your code to Yisheng Tang (yit311@lehigh.edu) no later than 11:59PM EST Monday February 6 (the day BEFORE the competition)

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Search Strategies

Search Strategies. CPS4801. Uninformed Search Strategies. Uninformed search strategies use only the information available in the problem definition Breadth-first search Uniform-cost search Depth-first search Depth-limited search Iterative deepening search. Breadth-first search.

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Artificial Intelligence Solving problems by searching

Artificial Intelligence Solving problems by searching. Fall 2008 professor: Luigi Ceccaroni. Problem solving. We want: To automatically solve a problem We need: A representation of the problem Algorithms that use some strategy to solve the problem defined in that representation.

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Solving problems by searching

Solving problems by searching. Chapter 3. Outline. Problem-solving agents Problem types Problem formulation Example problems Basic search algorithms. Example: vacuum world. Single-state , start in #5. Solution?. Example: vacuum world.

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Classic AI Search Problems

Classic AI Search Problems Sliding tile puzzles 8 Puzzle (3 by 3 variation) Small number of 8!/2, about 1.8 *10 5 states 15 Puzzle (4 by 4 variation) Large number of 16!/2 , about 1.0 *10 13 states 24 Puzzle (5 by 5 variation) Huge number of 25!/2 , about 7.8 *10 25 states

1.25k views • 43 slides

Classic AI Search Problems

Classic AI Search Problems. Sliding tile puzzles 8 Puzzle (3 by 3 variation) Small number of 8!/2, about 1.8 *10 5 states 15 Puzzle (4 by 4 variation) Large number of 16!/2 , about 1.0 *10 13 states 24 Puzzle (5 by 5 variation)

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Production systems and Control Strategies

Production systems and Control Strategies. Strategies. Control Strategies: It is a technique or strategy, tells us about which rule has to be applied next while searching for the solution of a problem within problem space

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Review: Search problem formulation

Review: Search problem formulation. Initial state Actions Transition model Goal state (or goal test ) Path cost What is the optimal solution? What is the state space?. Example 1: Romania. On vacation in Romania; currently in Arad Flight leaves tomorrow from Bucharest. Initial state

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Problem Solving By Searching

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Your chance to review

Your chance to review. Consider a state space where the start state is number 1 and the successor function for state n returns two states, numbers 2n and 2n+1. Draw the portion of the state space for states 1 to 15.

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Artificial Intelligent

Artificial Intelligent. Chapter 5 Blind / Un-informed Search. Uninformed search strategies. Uninformed search strategies use only the information available in the problem definition Breadth-first search Uniform-cost search Depth-first search Depth-limited search

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CSC 550: Introduction to Artificial Intelligence Fall 2004

CSC 550: Introduction to Artificial Intelligence Fall 2004. AI as search problem states, state spaces uninformed search strategies depth first search depth first search with cycle checking breadth first search breadth first search with cycle checking iterative deepening. AI as search.

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midterm review

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Announcements

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