Use k-nearest neighbor (k=3) with Manhattan distance to classify the node (2,3) with an unknown label as being class A or class B. The training data consists of the following nodes: Node1=(1,1), class A Node2=(0,0), class A Node3=(-1,2), class A Node4=(2,3), class B Node5=(0,-1), class B Node6=(7,10), class B In addition to the final classification, provide the answer for the Manhattan distance calculation between node (2,3) and node3 in the training data.

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Eight puzzle problem

The N-puzzle problem contains N tiles (N+1 including empty tiles) where the value of N can be 8, 15, 24, etc. The puzzle is divided into the square root of (N+1) rows and the square root of (N+1) columns. These problems have an initial state or configuration and a goal state or configuration. The puzzle can be solved by shifting the tiles one by one in the empty space. The objective is to place the numbers on the tiles to match the final state using the empty space. The other name for the N-puzzle problem is the sliding puzzle.