'Uniform cost search' diaporamas de présentation

Chapter 3 Best First Search

Chapter 3 Best First Search. Best First Search. So far, we have assumed that all the edges have the same cost, and that an optimal solution is a shortest path from the initial state to a goal state.

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Last time: search strategies

Last time: search strategies. Uninformed: Use only information available in the problem formulation Breadth-first Uniform-cost Depth-first Depth-limited Iterative deepening Informed: Use heuristics to guide the search Best first:

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CS 188: Artificial Intelligence

CS 188: Artificial Intelligence. Informed Search. Instructors: Dan Klein and Pieter Abbeel University of California, Berkeley [These slides were created by Dan Klein and Pieter Abbeel for CS188 Intro to AI at UC Berkeley. All CS188 materials are available at http:// ai.berkeley.edu .]. Today.

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CS 4100 Artificial Intelligence

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Review

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Lecture 3

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Artificial Intelligence 3. Search in Problem Solving

Artificial Intelligence 3. Search in Problem Solving. Course V231 Department of Computing Imperial College, London Jeremy Gow. Problem Solving Agents. Looking to satisfy some goal Wants environment to be in particular state Have a number of possible actions An action changes environment

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Artificial Intelligence

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Informed Search

Informed Search. Modified by M. Perkowski. Yun Peng. i. a. g. b. c. d. e. h. h= 1. h=2. h=1. h=1. h=0. h=1. h=1. f. h=0. All heuristic domain specific knowledge is in function h. Informed Methods Add Domain-Specific Information.

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Informed search strategies

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Informed Search chapter 4

Informed Search chapter 4. Informed Methods Add Domain-Specific Information. Add domain-specific information to select what is the best path to continue searching along Define a heuristic function, h(n), that estimates the "goodness" of a node n with respect to reaching a goal.

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Uninformed Search

Uninformed Search. ECE457 Applied Artificial Intelligence Spring 2007 Lecture #2. Outline. Problem-solving by searching Uninformed search techniques Russell & Norvig, chapter 3. Problem-solving by searching. An agent needs to perform actions to get from its current state to a goal .

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CSC3203: AI for Games Informed search (1)

CSC3203: AI for Games Informed search (1). Patrick Olivier p.l.olivier@ncl.ac.uk. Depth-first. Iterative deepening. Breadth-first. Uninformed search: summary. Informed search strategies. Best-first search Greedy best-first search A* search Local beam search Simulated annealing search

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Ch 3.5 and 3.6

Informed Search Algorithms Use problem-specific knowledge beyond the definition of the problem itself. Ch 3.5 and 3.6. Outline. Heuristic Search Methods Best-first search algorithms Greedy best-first search A * search Dominance Relaxed Problems. Heuristic Search Methods.

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For Wednesday

For Wednesday. Read chapter 5, sections 1-4 Homework: Chapter 3, exercise 23. Then do the exercise again, but use greedy heuristic search instead of A*. Program 1. Any questions?. Problem Formulation. States Initial state Actions Transition model Goal test Path cost.

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AI Algorithms

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A* Search

A* Search. What is an A* Search?.

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Shortest Path Algorithms

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Uniform Cost Search

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Uniform Cost Search

Uniform Cost Search. Introduction to AI. Uniform cost search.

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