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Search Strategies and Constraint Satisfaction Search

This lecture covers search strategies including generating action sequences, expanding states, search trees and graphs, and data structures for search trees. It also explores uninformed and informed search strategies, such as breadth-first and depth-first search, as well as constraint satisfaction search techniques like backtracking and forward checking. In the homework, students are tasked with implementing different search strategies and comparing their space and time complexities.

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Search Strategies and Constraint Satisfaction Search

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  1. Search 5주강의

  2. Generating action sequences • Generating a new set of states  expanding the state • Search strategy ::: the choice of which state to expand first • Search tree, Search graph • Data structures for search trees : Queue, Stack

  3. Search Strategies • Completeness ::: guaranteeing to find a solution where there is one • Time complexity • Space complexity • Optimality ::: to find the high quality solution ???

  4. Search Strategies • Uninformed (blind) search • Informed (heuristic) search

  5. Uninformed search I • Breadth-first search : branching factor : memory requirement • Uniform cost search : g(n). data structure : g(n) = depth(n)  breadth-first search

  6. Uninformed search II • Depth-first search : stack : ??? completeness  w+1 • Depth limit search • Iterative deepening search ::: depth를 증가하면서 depth limit search • Bi-directional Search

  7. 숙제 (기간:: 10월24일까지) • Missionary-cannibals 문제에 대해 (1) depth-first search로는 답을 구하지 못할 수 있음을 보여라 (2) depth-first search에 같은 sate가 다시 나타나면 제거하는 기능이 있으면 답을 구할 수 있다. 이를 프로그램하라. (3) breadth-first search로 구현하라. (4) iterative deepening 방법으로 구현하라. (5) (2), (3), (4)에 대해 space와 수행속도를 비교하라

  8. Comparing Search Strategies B: branching factor, d: depth of solution, m: maximum depth, l: depth limit

  9. Constraint Satisfaction Search • The states are defined by the values of a set of variables and the goal test specifies a set of constraints that must the values must obey • Cryptarithmetic, 8 queens problem, VLSI design • In CSP, the goal test is decomposed into a set of constraints on variables rather than being a blackbox

  10. Search in CSP • Depth-first search on a CSP wastes time searching when constraints have already been violated • Backtracking search • Forward checking ::: Each time a variable is instantiated, forward checking deletes from the domains of the as-yet-uninstantiated variables all of those values that conflict with the variables assigned • Constraints propagation

  11. 숙제 • 문제 3.2, 3.3, 3.5, 3.8, 3.11, 3.13, 3.14, 3.17, 3.20, 3.21

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