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Any any point in the game the amount of possible moves for a player is quite low* (around 5) this means that thinking a few moves ahead, evaluating every possible move and selecting the best move is doable.

This approach is called minimax (wikipedia).

To implement minimax you'll need a evaluation function that returns a score for a given board layout and player. For draughts a naive implementation would be a function that returns one point for every piece the player has alive.

A visualisation of a minimax decision tree (from the wikipedia article). Down the left hand side is the turn number. The leaf nodes each have an evaluated score which is fed back up the tree to make a decision.

* however draughts is the game with the highest branching factor that has been completely solved.

At any point in the game the amount of possible moves for a player is quite low* (around 5) this means that thinking a few moves ahead, evaluating every possible move and selecting the best move is doable.

This approach is called minimax (wikipedia).

To implement minimax you'll need a evaluation function that returns a score for a given board layout and player. For draughts a naive implementation would be a function that returns one point for every piece the player has alive.

A visualisation of a minimax decision tree (from the wikipedia article). Down the left hand side is the turn number. The leaf nodes each have an evaluated score which is fed back up the tree to make a decision.

* however draughts is the game with the highest branching factor that has been completely solved.

Any any point in the game the amount of possible moves for a player is quite low (around 5) this means that thinking a few moves ahead, evaluating every possible move and selecting the best move is doable.

This approach is called minimax (wikipedia).

To implement minimax you'll need a evaluation function that returns a score for a given board layout and player. For draughts a naive implementation would be a function that returns one point for every piece the player has alive.

A visualisation of a minimax decision tree (from the wikipedia article). Down the left hand side is the turn number. The leaf nodes each have an evaluated score which is fed back up the tree to make a decision.

Any any point in the game the amount of possible moves for a player is quite low* (around 5) this means that thinking a few moves ahead, evaluating every possible move and selecting the best move is doable.

This approach is called minimax (wikipedia).

To implement minimax you'll need a evaluation function that returns a score for a given board layout and player. For draughts a naive implementation would be a function that returns one point for every piece the player has alive.

A visualisation of a minimax decision tree (from the wikipedia article). Down the left hand side is the turn number. The leaf nodes each have an evaluated score which is fed back up the tree to make a decision.

* however draughts is the game with the highest branching factor that has been completely solved.

Any any point in the game the amount of possible moves for a player is quite low (around 5) this means that thinking a few moves ahead, evaluating every possible move and selecting the best move is doable.

This approach is called minimax (wikipedia).

To implement minimax you'll need a evaluation function that returns a score for a given board layout and player. For draughts a naive implementation would be a function that returns one point for every piece the player has alive.

Any any point in the game the amount of possible moves for a player is quite low (around 5) this means that thinking a few moves ahead, evaluating every possible move and selecting the best move is doable.

This approach is called minimax (wikipedia).

To implement minimax you'll need a evaluation function that returns a score for a given board layout and player. For draughts a naive implementation would be a function that returns one point for every piece the player has alive.

A visualisation of a minimax decision tree (from the wikipedia article). Down the left hand side is the turn number. The leaf nodes each have an evaluated score which is fed back up the tree to make a decision.