2048 is played on a 4x4 grid with numbered tiles which can slide up, down, left, or right. This game can be modeled as a two player game, in which the computer AI generates a 2- or 4-tile placed randomly on the board, and the player then selects a direction to move the tiles. Note that the tiles move until they either (1) collide with another tile, or (2) collide with the edge of the grid. If two tiles of the same number collide in a move, they merge into a single tile valued at the sum of the two originals. The resulting tile cannot merge with another tile again in the same move.

Usually, each role in a two-player games has a similar set of moves to choose from, and similar objectives (e.g. chess). In 2048 however, the player roles are inherently asymmetric, as the Computer AI places tiles and the Player moves them.

I used adversial search techniques and Expectiminimax algorithm to develop this game.

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To run the game,

python3 GameManager.py

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I used alpha-beta pruning and the below heuristics to improve the quality of gameplay.

This heuristic tries to ensure that the values of the tiles are all either increasing or decreasing along both the left/right and up/down directions. This heuristic alone captures the intuition that many others have mentioned, that higher valued tiles should be clustered in a corner. It will typically prevent smaller valued tiles from getting orphaned and will keep the board very organized, with smaller tiles cascading in and filling up into the larger tiles.

This heuristic alone tends to create structures in which adjacent tiles are decreasing in value, but of course in order to merge, adjacent tiles need to be the same value. Therefore, the smoothness heuristic just measures the value difference between neighboring tiles, trying to minimize this count.

A combination of the above heuristics are chosen with the weights being tuned to give the best results.

Reference: https://stackoverflow.com/questions/22342854/what-is-the-optimal-algorithm-for-the-game-2048

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