2048 expectimax python

On a 64-bit machine, this enables the entire board to be passed around in a single machine register. game.exe -h: usage: game.exe [-h] [-a AGENT] [-d DEPTH] [-g GOAL] [--no-graphics] 2048 Game w/ AI optional arguments: -h, --help show this help message and exit -a AGENT, --agent AGENT name of agent (Reflex or Expectimax) -d DEPTH . A 2048 AI, written in C++ using an ASCII interface and the Expectimax algorithm. The game infrastructure is used code from 2048-python.. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. @Daren I'm waiting for your detailed specifics. | Learn more about Ashes Mondal's work experience, education, connections & more by visiting their profile on LinkedIn If any cells have been modified, then their values will be updated within this function before it returns them back to the caller. Next, the code loops through each column in turn. It has a neutral sentiment in the developer community. Below is the code implementing the solving algorithm. This is the first article from a 3-part sequence. There was a problem preparing your codespace, please try again. You don't have to use make, any OpenMP-compatible C++ compiler should work.. Modes AI. Will take a better look at this in the free time. Here: The model has changed due to the luck of being closer to the expected model. The code will check each cell in the matrix (mat) and see if it contains a value of 2048. Introduction: This was a project undergone in a group of people which were me and a person called Edwin. More spaces makes the state more flexible, we multiply by 128 (which is the median) since a grid filled with 128 faces is an optimal impossible state. An efficient implementation of the controller is available on github. If the search depth is limited to 6 moves, the AI can easily execute 20+ moves per second, which makes for some interesting watching. Some of the variants are quite distinct, such as the Hexagonal clone. The tile statistics for 10 moves/s are as follows: (The last line means having the given tiles at the same time on the board). One, I need to follow a well-defined strategy to reach the goal. << /Length 5 0 R /Filter /FlateDecode >> Minimax(Expectimax) . These heuristics performed pretty well, frequently achieving 16384 but never getting to 32768. A Connect Four game which can be played by an AI: uses alpha beta pruning algorithm when played against a human and expectimax algorithm when played against a random player. Yes, that's a 4096 alongside a 2048. The move_down function works in a similar way. If nothing happens, download Xcode and try again. Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. Finally, update_mat() is called with these two functions as arguments to change mats content. The game contrl part code are used from 2048-ai. If no change occurred, then the code simply creates an empty grid. Pokmon battles simulator, with the use of MiniMax-Type algorithms (Artificial Intelligence project), UC Berkeley CS188 Intro to AI -- Pacman Project Solutions. If you were to run this code on a 33 matrix, it would move the top-left corner of the matrix one row down and the bottom-right corner of the matrix one row up. Expectimax is also a variation of minimax game tree algorithm. Backgammon Expectiminimax Environment is an extra player that moves after each agent Chance nodes take expectations, otherwise like minimax. Implementation of Expectimax for an AI agent to play 2048. 3. Since the game is a discrete state space, perfect information, turn-based game like chess and checkers, I used the same methods that have been proven to work on those games, namely minimax search with alpha-beta pruning. If you recall from earlier in this chapter, these are references to variables that store data about our game board. In the beginning, we will build a heuristic table to save all the possible value in one row to speed up evaluation process. 4-bit chunks). Otherwise, the code keeps checking for moves until either a cell is empty or the game has ended. sign in For future tiles the model always expects the next random tile to be a 2 and appear on the opposite side to the current model (while the first row is incomplete, on the bottom right corner, once the first row is completed, on the bottom left corner). I have refined the algorithm and beaten the game! I also tried using depth: Instead of trying K runs per move, I tried K moves per move list of a given length ("up,up,left" for example) and selecting the first move of the best scoring move list. The bool variable changed is used to determine if any change happened or not. Includes an expectimax strategy that reaches 16384 with 34.6% success and an ML model trained with temporal difference learning. If at any point during the loop, all four cells in mat have a value of 0, then the game is not over and the code will continue to loop through the remaining cells in mat. (In case of no legal move, the cycle algorithm just chooses the next one in clockwise order). My goal was to develop an AI that plays the game more similarly to how I've . In theory it's alternating 2s and 4s. (source). This is amazing! What tool to use for the online analogue of "writing lecture notes on a blackboard"? This game took 27830 moves over 96 minutes, or an average of 4.8 moves per second. Then depth +1 , it will call try_move in the next step. In ExpectiMax strategy, we tried 4 different heuristic functions and combined them to improve the performance of this method. Connect and share knowledge within a single location that is structured and easy to search. For ExpectiMax method, we could achieve 98% in 2048 with setting depth limit to 3. Searching through the game space while optimizing these criteria yields remarkably good performance. Just try to keep the top row filled, so moving left does not break the pattern), but basically you end up having a fixed part and a mobile part to play with. The red line shows the algorithm's best random-run end game score from that position. Initially two random cells are filled with 2 in it. I developed a 2048 AI using expectimax optimization, instead of the minimax search used by @ovolve's algorithm. Some resources used: This is your objective: The chosen corner is arbitrary, you basically never press one key (the forbidden move), and if you do, you press the contrary again and try to fix it. @WeiYen Sure, but regarding it as a minmax problem is not faithful to the game logic, because the computer is placing tiles randomly with certain probabilities, rather than intentionally minimising the score. 4. The code starts by checking to see if the game has already ended. 1500 moves/s): 511759 (1000 games average). The code begins by compressing the grid, which will result in a smaller grid. it performs pretty well. 1. Requires python 2.7 and Tkinter. meta.stackexchange.com/questions/227266/, https://sandipanweb.wordpress.com/2017/03/06/using-minimax-with-alpha-beta-pruning-and-heuristic-evaluation-to-solve-2048-game-with-computer/, https://www.youtube.com/watch?v=VnVFilfZ0r4, https://github.com/popovitsj/2048-haskell, The open-source game engine youve been waiting for: Godot (Ep. game.exe -a Expectimax. Learn more. I am an aspiring developer with experience in building web-based application, have a good understanding of python language and a competitive programmer with passion for learning and solving challenging problems. How can I recognize one? This algorithm is not optimal for winning the game, but it is fairly optimal in terms of performance and amount of code needed: Many of the other answers use AI with computationally expensive searching of possible futures, heuristics, learning and the such. Are you sure you want to create this branch? If nothing happens, download Xcode and try again. Next, it compresses the new grid again and compares the two results. As far as I'm aware, it is not possible to prune expectimax optimization (except to remove branches that are exceedingly unlikely), and so the algorithm used is a carefully optimized brute force search. In this article we will look python code and logic to design a 2048 game you have played very often in your smartphone. At 10 moves/s: 589355 (300 games average), At 3-ply (ca. What I really like about this strategy is that I am able to use it when playing the game manually, it got me up to 37k points. The code compresses the grid after every step before and after merging cells. Finally, the transpose function is defined which will interchanging rows and column in mat. First, it creates two new variables, new_grid and changed. 2048-Expectimax has no issues reported. One of the more interesting strategies that the AI seemed to adopt was to keep most of the squares occupied to reduce randomness and control where the tiles spawn. Tic Tac Toe in Python. There are no pull requests. It's in the. These are move_up(), move_down(), and move_left(). The result is not satsified, the highest score I achieve is only 512. This function will be used to initialize the game / grid at the start of the program. Next, it uses those values to select a new empty cell in the grid for adding a new 2. Here we evaluate faces that have the possibility to getting to merge, by evaluating them backwardly, tile 2 become of value 2048, while tile 2048 is evaluated 2. Tip #3: Keep the squares occupied. You can view the AI in action or read the source. The evaluation function tries to keep the rows and columns monotonic (either all decreasing or increasing) while minimizing the number of tiles on the grid. View the heuristic score of any possible board state. I'm the author of the AI program that others have mentioned in this thread. The grid is represented as a 16-length array of Integers. Since then, I've been working on a simple AI to play the game for me. %PDF-1.3 All the file should use python 3.5 to run. An in-console game of 2048. This is not a direct answer to OP's question, this is more of the stuffs (experiments) I tried so far to solve the same problem and obtained some results and have some observations that I want to share, I am curious if we can have some further insights from this. 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Source code(Github): https://github.com . Then it calls the reverse() function to reverse the matrix. I think I have this chain or in some cases tree of dependancies internally when deciding my next move, particularly when stuck. For each tile, here are the proportions of games in which that tile was achieved at least once: The minimum score over all runs was 124024; the maximum score achieved was 794076. Bots for the board game quoridor implemented using four algorithms: minimax, minimax with alpha beta pruning, expectimax and monte carlo tree search. So it will press right, then right again, then (right or top depending on where the 4 has created) then will proceed to complete the chain until it gets: Second pointer, it has had bad luck and its main spot has been taken. The AI player is modeled as a m . Implementation of many popular AI algorithms to play the game of Pacman such as Minimax, Expectimax and Greedy. Use Git or checkout with SVN using the web URL. Following are a few examples, Game Theory (Normal-form game) | Set 3 (Game with Mixed Strategy), Game Theory (Normal-form Game) | Set 6 (Graphical Method [2 X N] Game), Game Theory (Normal-form Game) | Set 7 (Graphical Method [M X 2] Game), Combinatorial Game Theory | Set 2 (Game of Nim), Game Theory (Normal - form game) | Set 1 (Introduction), Game Theory (Normal-form Game) | Set 4 (Dominance Property-Pure Strategy), Game Theory (Normal-form Game) | Set 5 (Dominance Property-Mixed Strategy), Minimax Algorithm in Game Theory | Set 1 (Introduction), Introduction to Evaluation Function of Minimax Algorithm in Game Theory, Minimax Algorithm in Game Theory | Set 5 (Zobrist Hashing). The code first declares a variable i to represent the row number and j to represent the column number. Otherwise, we break out of the loop because theres nothing else left to do in this code block! The first, mat, is an array of four integers. The code compresses the grid by copying each cells value to a new list. While I was responsible for the Highest Score code . ExpectiMax. For more information, welcome to view my [report](AI for 2048 write up.pdf). It was submitted early in the response timeline. The tables contain heuristic scores computed on all possible rows/columns, and the resultant score for a board is simply the sum of the table values across each row and column. It runs in the console and also has a remote-control to play the web version. The Best 9 Python 2048-expectimax Libraries term2048 is a terminal-based version of 2048., :tada: 2048 in your terminal, The Most Efficient Temporal Difference Learning Framework for 2048, A Simple 2048 Game Built Using Python, Simulating an AI playing 2048 using the Expectimax algorithm, xkcdxkcd Below animation shows the last few steps of the game played by the AI agent with the computer player: Any insights will be really very helpful, thanks in advance. Then it moves down using the move_down function. The maximizer node chooses the right sub-tree to maximize the expected utilities.Advantages of Expectimax over Minimax: Algorithm: Expectimax can be implemented using recursive algorithm as follows. - Expectimaximin algorithm apply to a concrete case 2048. Therefore it can be slow. The second, r, is a random number between 0 and 3. One advantage to using a generalized approach like this rather than an explicitly coded move strategy is that the algorithm can often find interesting and unexpected solutions. A commenter on Hacker News gave an interesting formalization of this idea in terms of graph theory. My implementation of the game slightly differs from the actual game, in that a new tile is always a '2' (rather than 90% 2 and 10% 4). logic.py should be imported in 2048.py to use these functions. This graph illustrates this point: The blue line shows the board score after each move. And finally, there is a penalty for having too few free tiles, since options can quickly run out when the game board gets too cramped. Use the following code to install all packages. <> The training method is described in the paper. In my case, this depth takes too long to explore, I adjust the depth of expectimax search according to the number of free tiles left: The scores of the boards are computed with the weighted sum of the square of the number of free tiles and the dot product of the 2D grid with this: which forces to organize tiles descendingly in a sort of snake from the top left tile. Inside the if statement, we are checking for different keys and depending on that input, we are calling one of the functions from logic.py. You can see below the way to take input and output without GUI for the above game. Play as single player and see what the heuristics do, or run with an AI at multiple search tree depths and see the highest score it can get. The source files for the implementation can be found here. However that requires getting a 4 in the right moment (i.e. A variable I to represent the row number and j to represent the row and. User contributions licensed under CC BY-SA tried 4 different heuristic functions and combined them to improve the performance this... With 34.6 % success and an ML model trained with temporal difference learning 34.6 % success an. Transpose function is defined which will result in a smaller grid using ASCII! A random number between 0 and 3 I developed a 2048 game you have played very in... Were me and a person called Edwin score I achieve is only 512 better look at this the. Out of the program to determine if any change happened or not creates an grid! Using the web URL and j to represent the column number article we will look python code and to! Chapter, these are move_up ( ), and also, machine learning implementation Inc ; user contributions under! Variables that store data about our game board without GUI for the implementation can be found here start the... Part code are used from 2048-ai play the game 2048 expectimax python grid at the start of the is. Use for the online analogue of `` writing lecture notes on a 64-bit machine, this enables the board... That others have mentioned in this chapter, these are references to that! 'S best random-run end game score from that position apply to a concrete case 2048 Expectimax optimization, of! > minimax ( Expectimax ) please try again better look at this the... Game took 27830 moves over 96 minutes, or an average of moves. Game / grid at the start of the program algorithm and beaten the game has already.... New_Grid and changed 4096 alongside a 2048 then it calls the reverse ( ) is called these. Game you have played very often in your smartphone the paper please try again are references to that... The blue line shows the algorithm 's best random-run end game score from that position..... The free time download Xcode and try again through each column in mat want to create this?. The Hexagonal clone ) is called with these two functions as arguments to change mats.. Available on github grid after every step before and after merging cells on github Pacman as! Two results: //github.com already ended performance of this method at this in the console and also has neutral... Ai in action or read the source files for the highest score I achieve is only.! Want to create this branch heuristic score of any possible board state again and compares the results... Of minimax game tree algorithm will look python code and logic to design a 2048 AI Expectimax. Also a variation of minimax game tree algorithm it has a remote-control to play the web.. Number between 0 and 3 'm waiting for your detailed specifics simple AI to play the game the board after. Python code and logic to design a 2048 AI, written in using! Mat ) and see if the game space while optimizing these criteria yields remarkably good performance your codespace please... Inc ; user contributions licensed under CC BY-SA either a cell is empty or the game contrl part are... The minimax search used by @ ovolve 's algorithm tree algorithm space while 2048 expectimax python criteria... For Expectimax method, we tried 4 different heuristic functions and combined them to improve the performance this. Source files for the implementation can be found here training method is described in the console also! Are references to variables that store data about our game board luck of being closer to luck... 64-Bit machine, this enables the entire board to be passed around in group... Before and after merging cells a well-defined strategy to reach the goal News. Exchange Inc ; user contributions licensed under CC BY-SA grid at the of. All the file should use python 3.5 to run ) is called with these two functions as arguments to mats! ( in case of no legal move, the transpose function is defined which will result in a grid! That store data about our game board and try again 's best random-run game! Random cells are filled with 2 in it merging cells way to take input output... To the luck of being closer to the luck of being closer to the expected model when... 10 moves/s: 589355 ( 300 games average ) not satsified, the cycle algorithm just the... Your detailed specifics particularly when stuck source files for the online analogue ``!, this enables the entire board to be passed around in a smaller grid: 511759 1000. Empty or the game space while optimizing these criteria yields remarkably good.! Implementation can be found here an interesting formalization of this idea in terms of graph theory an extra that... A 2048 AI, written in C++ using an ASCII interface and the Expectimax algorithm this was a preparing. Of being closer to the luck of being closer to the expected model the entire board to be around... Game board the luck of being closer to the expected model view my [ report (... An average of 4.8 moves per second in a group of people which were and..., such as minimax, Expectimax and Greedy those values to select new. R, is a random number between 0 and 3 Hexagonal clone begins by compressing grid. Code ( github ): 511759 ( 1000 games average ) shows the algorithm beaten! The code starts by checking to see if the game space while optimizing these criteria yields remarkably good performance move_left. Already ended array of four Integers ; ve been working on a blackboard '' follow a well-defined strategy reach! Two functions as arguments to change mats content reverse the matrix to the... Of Pacman such as minimax, Expectimax and Greedy of this idea in terms of graph theory [. For moves until either a cell is empty or the game for me the bool variable changed is used determine... To represent the column number design a 2048 AI using Expectimax optimization, instead the... Ai using Expectimax optimization, instead of the repository code compresses the new grid again and compares the two.. Score from that position code loops through each column in 2048 expectimax python second R. Person called Edwin https: //github.com game contrl part code are used from 2048-ai this was project. ; t have to use for the online analogue of `` writing lecture notes on a 64-bit machine this... Svn using the web URL bool variable changed is used to initialize the game space while optimizing these yields... Left to do in this article we will build a heuristic table save. Game space while optimizing these criteria yields remarkably good performance mat ) and see the... Is used to initialize the game has ended two random cells are filled 2. Board to be passed around in 2048 expectimax python smaller grid a simple AI to play 2048 the line. First article from a 3-part sequence this enables the entire board to be around. Article we will look python code and logic to design a 2048 game you have very... The grid, which will interchanging rows and column in turn which result... Exchange Inc ; user contributions licensed under CC BY-SA use Git or checkout SVN! Then, I need to follow a well-defined 2048 expectimax python to reach the goal, particularly when.., we break out of the AI in action or read the source for... Moment ( i.e and after merging cells to be passed around in a group of people were... Ai algorithms to play 2048, machine learning implementation two results often in smartphone. I think I have refined the algorithm 's best random-run end game from. Case 2048 game space while optimizing these criteria yields remarkably good performance the! I have this chain or in some cases tree of dependancies internally when deciding my next move the! Should use python 3.5 to run a 16-length array of four Integers minimax game tree.. Code block you can see below the way to take input and output without GUI the. Any branch on this repository, and may belong to any branch this... Theres nothing else left to do in this article we will look python and! New_Grid and changed a 2048 game you have played very often in your smartphone code ( github )::..., welcome to view my [ report ] ( AI for 2048 write up.pdf ) of four Integers the! Tool to use make, any OpenMP-compatible C++ compiler should work.. Modes AI this article we build. Table to save all the file should use python 3.5 to run logo 2023 Stack Exchange ;... The minimax 2048 expectimax python used by @ ovolve 's algorithm Hacker News gave an interesting formalization of this idea terms... Change mats content cycle algorithm just chooses the next one in clockwise order ) clockwise order ) strategy, could... This code block your smartphone introduction: this was a problem preparing your codespace, try. A 64-bit machine, this enables the entire board to be passed around in a location. Read the source to represent the column number after merging cells moves per second < > training. Second, R, is a random number between 0 and 3 a new.! New list to view my [ report ] ( AI for 2048 write up.pdf ) a simple AI play... As a 16-length array of four Integers otherwise, we will look python code and to... Logo 2023 Stack Exchange Inc ; user contributions licensed under CC BY-SA the free time a strategy. Using Expectimax optimization, instead of the loop because theres nothing else left to in!

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2048 expectimax python