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The top documents tagged [single current state]
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Informed search algorithms Chapter 4. Material Chapter 4 Section 1 - 3 Exclude memory-bounded heuristic search
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Local Search Algorithms Chapter 4. Outline Hill-climbing search Simulated annealing search Local beam search Genetic algorithms Ant Colony Optimization
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LOCAL SEARCH AND CONTINUOUS SEARCH. Local search algorithms In many optimization problems, the path to the goal is irrelevant ; the goal state itself
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Local search algorithms In many optimization problems, the state space is the space of all possible complete solutions We have an objective function that
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Two types of search problems Start state is given Goal state is known ahead of time Solution path matters No specific start state Goal state is unknown
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CS 561, Sessions 8-9 1 Last time: search strategies Uninformed: Use only information available in the problem formulation Breadth-first Uniform-cost Depth-first
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Lecture4(Search) (1)
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Informed Search Next time: Search Application Reading: Machine Translation paper under Links Username and password will be mailed to class
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1 CS 2710, ISSP 2610 R&N Chapter 4.1 Local Search and Optimization
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1 Local search and optimization Local search= use single current state and move to neighboring states. Advantages: –Use very little memory –Find often
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An Introduction to Artificial Life Lecture 4b: Informed Search and Exploration Ramin Halavati (
[email protected]
) In which we see how information
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Local Search Algorithms
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