A knowledge$-$based agent $($KBA$)$ combines general knowledge with current percepts to infer hidden aspects of the state prior to selecting actions. Inference means deriving new sentences from old ones.

In this section, you will solve an exercise to emulate how a knowledge$-$based agent infers knowledge from the current state in a Minesweeper game.

Minesweeper Rules:

The board is divided into cells, with mines randomly distributed. To win, the logical agent needs to open all the cells. The number on a cell shows the number of mines adjacent to it$.$ Using this information, the agent must determine cells that are safe, and cells that contain mines.

If you want to get familiar with minesweeper, you can play it here: online

$7.$ Inference

The next board contains $7$ mines, and each coordinate cell is labeled $($ x$,$y $)$ as a Cartesian plane.

Suppose you have implemented a knowledge$-$based agent and start to analyze the current state, place a flag in the cells in which the agent can determine with certainty that there is a mine.

$8.$ Logical Sentences :

For this exercise, read this information: Github

Formulate the agent knowledge as logical sentence for exercise $7.$ Each cell will be labeled as the concatenation of the $($x$,$y$)$ coordinates, for instance, cell $(3,4)$ is $34,$ cell $5,1$ is $51$ and so on$.$

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