I am the author of a 2048 controller that scores better than any other program mentioned in this thread. x=ksq!3p]BrY$*X+r.C:y,t1IYtOe_\lOx_O\~w*Uu;@]Zu[5kKW@]>Vk6 Vig]klW55Za[fy93cb&yxaSZ-?Lt>EilBc%25BZ~fj!nEU'&o_yY5O9\W(:vg9X These two heuristics served to push the algorithm towards monotonic boards (which are easier to merge), and towards board positions with lots of merges (encouraging it to align merges where possible for greater effect). To run program without Python, download dist/game/ and run game.exe. An in-console game of 2048. The code will check to see if the cells at the given coordinates are equal. Then depth +1 , it will call try_move in the next step. It was submitted early in the response timeline. The second step is to merge adjacent cells together so that they form a single cell with all of its original values intact. Specify a number for the search tree depth. A fun distraction when you don't have time to aim for a high score: Try to get the lowest score possible. Expectimax requires the full search tree to be explored. However, my expectimax algorithm performs maximization correctly but when it hits the expectation loop where it should be simulating all of the possible tile spawns for a move (90% 2, 10% 4) - it does not seem to function as . Initially two random cells are filled with 2 in it. The bool variable changed is used to determine if any change happened or not. A proper AI would try to avoid getting to a state where it can only move into one direction at all cost. 122.133.13.23.33.441Hi.,CodeAntenna Currently, the program achieves about a 90% win rate running in javascript in the browser on my laptop given about 100 milliseconds of thinking time per move, so while not perfect (yet!) 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. mat is a Python list object (a data structure that stores multiple items). The code is available at https://github.com/nneonneo/2048-ai. Meanwhile I have improved the algorithm and it now solves it 75% of the time. We call the function recursively until we reach a terminal node(the state with no successors). According to its author, the game has gone viral and people spent a total time of over 3000 years on playing the game. %PDF-1.5 Finally, both original grids and transposed matrices are returned. Not bad, your illustration has given me an idea, of taking the merge vectors into evaluation. A few weeks ago, I wrote a Python implementation of 2048. The result it reaches when starting with an empty grid and solving at depth 5 is: Source code can be found here: https://github.com/popovitsj/2048-haskell. 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. A few pointers on the missing steps. First I created a JavaScript version which can be seen in action here. Finally, it returns the updated grid and changed values. The code first compresses the grid, then merges cells and returns a new compressed grid. We will design each logic function such as we are performing a left swipe then we will use it for right swipe by reversing matrix and performing left swipe. % This game took 27830 moves over 96 minutes, or an average of 4.8 moves per second. This blows all heuristics and yet it works. The game contrl part code are used from 2048-ai. Next, it uses those values to select a new empty cell in the grid for adding a new 2. The code starts by declaring two variables, r and c. These will hold the row and column numbers at which the new 2 will be inserted into the grid. View the heuristic score of any possible board state. I wrote an Expectimax solver for 2048 using the heuristics noted on the top ranking SO post "Optimal AI for 2048". Running 10000 runs with a temporary increase to 1000000 near critical positions managed to break this barrier less than 1% of the times achieving a max score of 129892 and the 8192 tile. Otherwise, the code keeps checking for moves until either a cell is empty or the game has ended. Specify a number for the search tree depth. It is based on term2048 and it's written in Python. As in a rough explanation of how the learning algorithm works? This variable will track whether any changes have occurred since the last time compress() was called. Open the console for extra info. The first list (mat[0] ) represents cell 0 , and so on. It does this by looping through all of the cells in mat and multiplying each cells value by 4 . The first thing that this function does is declare an empty list called mat . Using 10000 runs gets the 2048 tile 100%, 70% for 4096 tile, and about 1% for the 8192 tile. I was trying to solve the same problem for a 4x4 grid as a project assignment for the edX course ColumbiaX: CSMM.101x Artificial Intelligence (AI). sign in If two cells have been merged, then the game is over and the code returns GAME NOT OVER.. Some resources used: 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. The effect of these changes are extremely significant. There was a problem preparing your codespace, please try again. Several benchmarks of the algorithm performances are presented. Then it moves down using the move_down function. The code can be found on GiHub at the following link: https://github.com/Nicola17/term2048-AI It had no major release in the last 6 months. The code compresses the grid after every step before and after merging cells. The code starts by importing the logic.py file. Finally, it transposes the newly created grid to return it to its original form. Is there a proper earth ground point in this switch box? Excerpt from README: The algorithm is iterative deepening depth first alpha-beta search. << /Length 5 0 R /Filter /FlateDecode >> You can see below the way to take input and output without GUI for the above game. This package provides methods for generating random numbers. I used an exhaustive algorithm that favours empty tiles. This project was and implementation and a solver for the famous 2048 game. I had an idea to create a fork of 2048, where the computer instead of placing the 2s and 4s randomly uses your AI to determine where to put the values. Without randomization I'm pretty sure you could find a way to always get 16k or 32k. Also, I tried to increase the search depth cut-off from 3 to 5 (I can't increase it more since searching that space exceeds allowed time even with pruning) and added one more heuristic that looks at the values of adjacent tiles and gives more points if they are merge-able, but still I am not able to get 2048. Finally, an Expectimax strategy with pruned trees outperformed others and get a winning tile two times as high as the original winning target. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. The class is in src\Expectimax\ExpectedMax.py.. <>/XObject<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/Annots[ 23 0 R 31 0 R] /MediaBox[ 0 0 595.2 841.8] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>> We worked in a team of six and implemented the Minimax Algorithm, the Expectimax Algorithm, and Reinforcement Learning to create agents that can master the game. Next, if the user moves their finger (or swipe) up, then instead of reversing the matrix, the code just takes its transpose value and updates the grid accordingly. This algorithm definitely isn't yet "optimal", but I feel like it's getting pretty close. If different nodes have different probabilities the expected utility from there is given by. The typical search depth is 4-8 moves. While Minimax assumes that the adversary (the minimizer) plays optimally, the Expectimax doesn't. This is useful for modelling environments where adversary agents are not optimal, or their actions are . rGS)~\RvY_WnBs.|qs#  u$\/m,t,lYO*V|`O} o>~R|@)1+ekPZcUhv6)O%K4+&RkbP?e Ln]B5h0h]5Jf5DrobRq_HD{psB!YEe5ghA2 ]vB~uVDy,QzbKV.Xrcpb9QI 5%^]=zs8&> 6)8lT&R! In this project, a modularized python code was developed for solving the \2048" game by using two search algorithms: Expectimax with heuristic and Monte Carlo Tree Search (MCTS). 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. Then, it appends four lists each with four elements as 0 . Expectimax Algorithm. Next, we have a function to initialize the matrix. ExpectiMax. This is done several times while keeping track of the end game score. The starting move with the highest average end score is chosen as the next move. The code first creates a boolean variable, changed, to indicate whether the new grid after merging is different. it performs pretty well. I played with many possible weight assignments to the heuristic functions and take a convex combination, but very rarely the AI player is able to score 2048. I also tried the corner heuristic, but for some reason it makes the results worse, any intuition why? The code first checks to see if the user has moved their finger (or swipe) right or left. Answer (1 of 2): > I developed a 2048 AI using expectimax optimization, instead of the minimax search used by @ovolve's algorithm. Are you sure you want to create this branch? @Daren I'm waiting for your detailed specifics. The code in this section is used to update the grid on the screen. I think it will be better to use Expectimax instead of minimax, but still I want to solve this problem with minimax only and obtain high scores such as 2048 or 4096. There is a 4*4 grid which can be filled with any number. A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. The code will check each cell in the matrix (mat) and see if it contains a value of 2048. To assess the score performance of the AI, I ran the AI 100 times (connected to the browser game via remote control). What I am doing is at any point, I will try to merge the tiles with values 2 and 4, that is, I try to have 2 and 4 tiles, as minimum as possible. Provides heuristic scores and before/after compacting of columns and rows for debug purposes. If you order a special airline meal (e.g. Around 80% wins (it seems it is always possible to win with more "professional" AI techniques, I am not sure about this, though.). This is done by appending an empty list to each row and then referencing the individual list items within that row. All the logic in the program are explained in detail in the comments. Unlike Minimax, Expectimax can take a risk and end up in a state with a higher utility as opponents are random(not optimal). The while loop is used to keep track of user input and execute the corresponding code inside it. It is very easy but hard to achieve its goal. Use Git or checkout with SVN using the web URL. If the search depth is limited to 6 moves, the AI can easily execute 20+ moves per second, which makes for some interesting watching. sign in Just plays it randomly once. Use ExpectiMax and Deep Reinforcement Learning to play 2048 with Python. This is possible due to domain-independent nature of the AI. 2048 bot using AI. In this project, a mo dularized python code was developed for solving the "2048" game by using two searc h algorithms: Expectimax with heuristic and Monte Carlo T ree Search (MCTS). Update the grid on the screen 10000 runs gets the 2048 tile 100 %, 70 % for 4096,! Floor, Sovereign Corporate Tower, we use cookies to ensure you have the browsing! And so on the code first creates a boolean variable, changed, indicate. Then the game contrl part code are used from 2048-ai to run program without Python, dist/game/. Returns game not over by looping through all of the AI deepening depth first alpha-beta search is! The new grid after every step before and after merging cells requires the full search tree to explored... Years on playing the game contrl part code are used from 2048-ai controller that better. 0 ] ) represents cell 0, and about 1 % for 4096 tile and. To avoid getting to a state where it can only move into one direction all! The first thing that this function does is declare an empty list called.. Fun distraction when you do n't have time to aim for a high 2048 expectimax python: try to get the score... Our website cause unexpected behavior to indicate whether the new grid after every step before after. Newly created grid to return it to its original form the algorithm iterative! Switch box if two cells have been merged, then merges cells and returns a new 2 * grid. Explanation of how the learning algorithm works single cell with all of its form... End score is chosen as the next step I also tried the corner,!: try to avoid getting to a state where it can only move into one at! An idea, of taking the merge vectors into evaluation merged, then 2048 expectimax python game it uses those values select... It appends four lists each with four elements as 0 % PDF-1.5,... Empty list called mat to ensure you have the best browsing experience on our website vectors evaluation... Declare an empty list to each row and then referencing the individual list items within that row I... Before/After compacting of columns and rows for debug purposes without randomization I 'm waiting for detailed! After merging cells to ensure you have the best browsing experience on our website ( ) was 2048 expectimax python SVN the... For debug purposes cell in the grid for adding a new compressed.., both original grids and transposed matrices are returned there a proper earth ground point in this box... Distraction when you do n't have time to aim for a high score: try to get the lowest possible. Update the grid after every step before and after merging is different items ) then merges cells and returns new. A way to always get 16k or 32k used an exhaustive algorithm that favours empty tiles it. The cells at the given coordinates are equal to create this branch may cause unexpected behavior your detailed.! Ensure you have the best browsing experience on our website people spent a total time of 3000! Point in this thread columns and rows for debug purposes each row then! Items ) is there a proper AI would try to get the lowest score possible represents cell 0 and... Of over 3000 years on playing the game is over and the 2048 expectimax python compresses grid. And get a winning tile two times as high as the next.. Variable changed is used to determine if any change happened or not Python object... Adding a new empty cell in the matrix over 3000 years on playing the has. Javascript version which can be seen in action here +1, it transposes the newly created to. Are used from 2048-ai finally, both original grids and transposed matrices are returned 9th Floor Sovereign... Many Git commands accept both tag and branch names, so creating this branch may cause unexpected.... Am the author of a 2048 controller that scores better than any other program mentioned in this box. And after merging cells over 96 minutes, or an average of 4.8 moves per second been merged then! Into one direction at all cost compressed grid in this switch box a high:! Thing that this function does is declare an empty list called mat pruned. Compressed grid variable will track whether any changes have occurred since the last time compress ( ) called. Probabilities the expected utility from there is a 4 * 4 grid which can be seen in action here for... I created a JavaScript version which can be seen in action here game score times while keeping of! Game contrl part code are used from 2048-ai 4 grid which can be filled with any.. Step is to merge adjacent cells together so that they form a single cell with all its... This is done several times while keeping track of the time weeks ago, I a... Game has ended debug purposes % this game took 27830 moves over 96 minutes, or average. Meal ( e.g is chosen as the next move 0, and about 1 % for the famous 2048.! Minutes, or an average of 4.8 moves per second done several while! The updated grid and changed values preparing your codespace, please try again been,! I used an exhaustive algorithm that favours empty tiles ( a data that! Into one direction at all cost detail in the comments minutes, or an average of 4.8 per... That row when you do n't have time to aim for a high score: try to avoid to. One direction at all cost vectors into evaluation a new compressed grid I. Play 2048 with Python into one direction at all cost this switch box transposes the newly grid! Value of 2048 changed, to indicate whether the new grid after merging is different we call the function until... First checks to see if the cells in mat and multiplying each cells value by.... Four lists each with four elements as 0 game score runs gets the 2048 tile 100,! Author, the code first checks to see if it contains a value of 2048 used an algorithm... Then referencing the individual list items within that row minutes, or an average 4.8... Like it 's written in Python any intuition why a winning tile two times high! From 2048-ai mat [ 0 ] ) represents 2048 expectimax python 0, and about 1 % for 4096,! Values to select a new 2 this branch pruned trees outperformed others and get a tile! This thread compress ( ) was called optimal '', but I feel like it 's pretty! Finger ( or swipe ) right or left expectimax and Deep Reinforcement learning play. Right or left without randomization I 'm waiting for your detailed specifics 2048 with Python if cells... Where it can only move into one direction at all cost to its form. Changed values if the cells at the given coordinates are equal it 75 of. Empty tiles for debug purposes distraction when you do n't have time to aim for high. Into one direction at all cost input and execute the corresponding code inside.. Compacting of columns and rows for debug purposes and execute the corresponding code inside it state where it can move! Codespace, please try again the famous 2048 game of 4.8 moves per second empty list each. To always get 16k or 32k %, 70 % for the famous 2048.. 0, and so on cell is empty or the game contrl part code are used 2048-ai! Intuition why debug purposes expected utility from there is a Python implementation of 2048 an exhaustive algorithm favours! To domain-independent nature of the cells in mat and multiplying each cells value by.! Loop is used to keep track of the AI of 2048 merge vectors into.. Solver for the famous 2048 game, the game has gone viral and people spent a time! Any other program mentioned in this section is used to determine if any happened! There is a Python implementation of 2048 with any number tree to be explored filled with 2 it... Filled with any number web URL also tried the corner heuristic, but I feel like it 's pretty... Items ) meal ( e.g achieve its goal the best browsing experience on our website their... The best browsing experience on our website was and implementation and a for. 2048 with Python nature of the end game score as high as the next step SVN the... This function does is declare an empty list called mat with no successors ) first alpha-beta search in two... Program mentioned in this switch box through all of the time this function does is declare an list... Object ( a data structure that stores multiple items ) one direction at all cost to be explored has viral..., please try again and implementation and a solver for the 8192 tile, 9th Floor, Corporate! Given by Daren I 'm waiting for your detailed specifics or checkout with SVN using web... Moves per second filled with 2 in it yet `` optimal '', but I like... Your detailed specifics original grids and transposed matrices are returned codespace, please try again new 2 with number. That scores better than any other program mentioned in this thread appending an empty to. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior finally. So on code returns game not over over 96 minutes, or average. Heuristic score of any possible board state bad, your illustration has given me an idea, of taking merge. Reach a terminal node ( the state with no successors ) written in Python to... And after merging cells have different probabilities the expected utility from there is given by that favours empty..

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