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Random Snake

This exploration of the classic Snake game by Harrison Tsai showcases how random walks and probability influence the snake's movement. By applying techniques like sticking probability, we can manipulate the snake's behavior, guiding it towards higher probability paths. The implementation respects periodic boundaries, maintains a constant size, and avoids penalties for overlap, preserving the game’s randomness. This study highlights the evolution of Snake from an arcade staple in the late 70s to a pre-loaded favorite on Nokia phones in 1998 while maintaining a steady frame rate of 200.

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Random Snake

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  1. Random Snake Harrison Tsai

  2. Random Walks, DLA • Uses probability to determine its next step • Probabilities can be manipulated to change behavior (e.g. with “sticking probability”, snake tends to go in the direction with higher probability) • Used periodic boundaries • Snake originated in arcades in the late 70s and became the standard pre-loaded game on Nokia phones in 1998 • Noticeable differences: constant size and no penalty for overlap. This is to keep the movie at a constant 200 frames and preserves randomness

  3. Run my code with: Matlab command line>> random_snake • random_snake.m • advance.m • place_body.m • pure_probability.m • straight_sense.m • quadrant_quest.m

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