文件列表:

ai.go (3045, 2017-03-31)
board.go (2326, 2017-03-31)
cell.go (513, 2017-03-31)
clock.go (871, 2017-03-31)
genetic-prog (0, 2017-03-31)
genetic-prog\genetic.cpp (2484, 2017-03-31)
getdata.go (343, 2017-03-31)
greedy_ai.go (877, 2017-03-31)
mino.go (2718, 2017-03-31)
mino_test.go (2590, 2017-03-31)
moves.go (506, 2017-03-31)
output.gif (10938352, 2017-03-31)
ranking.go (1383, 2017-03-31)
tetris-data (0, 2017-03-31)
tetris-data\ai-avg (38, 2017-03-31)
tetris-data\aiaggrh-avg (37, 2017-03-31)
tetris-data\aiexe (2967912, 2017-03-31)
tetris-data\ailines-avg (38, 2017-03-31)
tetris-data\greedy-avg (37, 2017-03-31)
tetris-data\greedyexe (2967744, 2017-03-31)
tetris-data\randexe (2967248, 2017-03-31)
tetris-data\random-avg (36, 2017-03-31)
tetris.go (2518, 2017-03-31)
view.go (5089, 2017-03-31)

# NextGen-Tetris  The aim of this project is to understand how different AI strategies perform while playing a game of Tetris on a 10x18 board. The end gold standard of the AI being a genetic programming algorithm which should ideally be able to play on for ages! ## Analysis Randomized bot (makes random choices): * Average score: 166 * Number of trials: 6685 * Sum: 1111315 Greedy bot (makes greedy choices, i.e. selects the move which maximizes the score): * Average: 210 * Number: 10000 * Sum: 2105309 Bot that minimizes the maximum height at every step: * Average: 726 * Number: 10049 * Sum: 7300***9 Prev bot + awards line clears: * Average: 1382 * Number: 9281 * Sum: 12831920 ## Tetris Shoutout to https://github.com/k0kubun/ for the Tetris shell!

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