- #TETRIS FRIENDS PLAY WITH FRIENDS HOW TO#
- #TETRIS FRIENDS PLAY WITH FRIENDS GENERATOR#
- #TETRIS FRIENDS PLAY WITH FRIENDS CODE#
This is far greater than the number of possible different Tetromino sequences (65536), so given the first 9 pieces of a game we can work out the unique seed that generated that sequence.Ģ 16 is a small enough value that we can enumerate the first 9 pieces for every seed and then find a match. This means that there are 7! * 7 (35280) possible combinations of the first 8 pieces in a game of Tetris, for 9 pieces there are 7! * 7 * 6 possible combinations (211680). The Adobe documentation states that Math.random() generates a floating point value between greater than 0.0 and less 1.0, multiplying this by 65536 and truncating the result to produce and integer leaves only 2 16 potential seeds, and subsequently only 2 16 possible streams of Tetrominoes.Īs I explained above, Tetris Bags can contain 5040 different possible combinations of Tetrominoes, after they are depleted the next generated Tetris piece can be any of the 7 possible tetrominoes. Perhaps this was for the best, as the alternative solution required a lot less work on my part. Initially I looked into the workings of the Math.random() function, however the underlying implementation of the Math.random() call is not specified in the Adobe documentation. This.mTetrisGameSeed = int((Math.random() * 65536))
Tetris Friends Tetris Bagsīelow is the constructor of the TetPieceBag class, TetPieceBag class implements the Tetris Bag mechanics as described above, refilling itself every time it is emptied with 7 new pieces generated using the m_RandomGenerator property.
#TETRIS FRIENDS PLAY WITH FRIENDS CODE#
I directly ported the TetRandom class to Python, I won't even pretend to understand exactly what the code is doing, but it seems to be a strange variation of a Mersenne Twister. Once Tetris Friends provide a custom seed they can use predictable stream of Tetrominoes in debugging, testing and in multiplayer games.
#TETRIS FRIENDS PLAY WITH FRIENDS GENERATOR#
However, a custom random number generator enables use of their own seed, a facility not provided by the Adobe Math class. The Tetris Friends random number generator was helpfully named "TetRandom", at first it seemed interesting that Tetris Friends had chosen to implement their own random number generator instead of using the built-in "Math.Random()". Tetris Friends games are all Flash based, and as such were easy to decompile using ShowM圜ode.com, some local variable names were lost but the meanings were easy enough to deduce. Tetris Friendsįiguring that Tetris Friends used some form of Psuedorandomness under the hood to refill the Tetromino bags, if I could reimplement the random number generator used in Tetris Friends It would be easy to predict the incoming stream of Tetrominoes given its initial starting conditions. The order of the pieces in a newly generated Tetromino bag should be generated randomly but true randomness is hard to achieve, especially with computers. So, from a given "Tetromino bag" there are only 7! (5040) different ways in which pieces can be removed. After one of each tetromino has been removed from the bag it is refilled again. It's simple enough to understand, every seven pieces generated during a game are chosen as if they are picked from a bag containing all of the possible pieces. When playing a game of Tetris, the stream of tetrominoes generated by the game typically follows the Random Generator algorithm described in the Tetris guideline.
#TETRIS FRIENDS PLAY WITH FRIENDS HOW TO#
Here in part one of this series I'll describe the process of predicting all the future pieces in a Tetris Friends game and then go into further developments and how to use our new stream of tetrominoes to make gameplay decisions in my next blog post on this topic. I was curious to see what could be done with a bot if you could predict and generate an infinite stream of the future tetrominoes in a game of Tetris. However when we play Tetris, the game itself imposes a hard limit on how far we are able see into the future, the preview provided is typically only in the range of 1 to 5 pieces. When developing bots for classical games such as Chess and Checkers the depth to which the engine evaluates the game tree is limited by the amount of time and by computing power.
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