Write a program which performs a breadth-first search to find the solution to any given board position for 15 puzzle Input The input should be given in the form of a sequence of numbered tiles for initial board configuration, '0' indicating the empty space (see example below) Output 1. Moves 2. Number of Nodes expanded 3. Time Taken 4. Memory Used Example >1024573896 11 12 13 10 14 15 Moves: RDLDDRR Number of Nodes expanded: 361 Time Taken: 0.238 Memory Used: 704kb Hint • You can use hashset to keep track of explored nodes and fast lookup

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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Use Python. Pseducode code is given. The input is in the example part and the expected output should be like the  example.

Write a program which performs a breadth-first search to find the solution to any given
board position for 15 puzzle
Input
The input should be given in the form of a sequence of numbered tiles for initial board
configuration, '0' indicating the empty space (see example below)
Output
1. Moves
2. Number of Nodes expanded
3. Time Taken
4. Memory Used
Example
> 1024573 896 11 12 13 10 14 15
Moves: RDLDDRR
Number of Nodes expanded: 361
Time Taken: 0.238
Memory Used: 704kb
Hint
You can use hashset to keep track of explored nodes and fast lookup
Transcribed Image Text:Write a program which performs a breadth-first search to find the solution to any given board position for 15 puzzle Input The input should be given in the form of a sequence of numbered tiles for initial board configuration, '0' indicating the empty space (see example below) Output 1. Moves 2. Number of Nodes expanded 3. Time Taken 4. Memory Used Example > 1024573 896 11 12 13 10 14 15 Moves: RDLDDRR Number of Nodes expanded: 361 Time Taken: 0.238 Memory Used: 704kb Hint You can use hashset to keep track of explored nodes and fast lookup
Figure 3.9
function
BREADTH-FIRST-SEARCH(problem)
node + NODE(problem.INITIAL)
if problem.IS-GOAL(node.STATE)
frontiera FIFO queue, with node as an element
reached{problem. INITIAL}
then return node
while not IS-EMPTY(frontier) do
node POP(frontier)
for each child in EXPAND(problem, node) do
s+child.STATE
returns a solution node or failure
if problem.IS-GOAL(s) then return child
if s is not in reached then
add s to reached
add child to frontier
return failure
function UNIFORM-COST-SEARCH(problem) returns a solution node, or failure
return BEST-FIRST-SEARCH(problem, PATH-COST)
Transcribed Image Text:Figure 3.9 function BREADTH-FIRST-SEARCH(problem) node + NODE(problem.INITIAL) if problem.IS-GOAL(node.STATE) frontiera FIFO queue, with node as an element reached{problem. INITIAL} then return node while not IS-EMPTY(frontier) do node POP(frontier) for each child in EXPAND(problem, node) do s+child.STATE returns a solution node or failure if problem.IS-GOAL(s) then return child if s is not in reached then add s to reached add child to frontier return failure function UNIFORM-COST-SEARCH(problem) returns a solution node, or failure return BEST-FIRST-SEARCH(problem, PATH-COST)
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