#SCREEN SNAKE HOW TO#
The agent will learn how to play SS without us ever having to explicitly teach it. Over time, by reinforcing positive actions and disincentivizing negative actions, the agent will start to figure out the best strategies to get more positive rewards. Whenever the agent does something negative (like collide with a wall), we punish it. We let the agent play randomly and whenever it does something positive (like get a fruit) we reward it.
#SCREEN SNAKE TRIAL#
Rules like “if collision is imminent, turn left” or “if moving away from fruit, turn around.” This would be quite difficult and take a lot of time.Īnother option is to get the agent to learn by trial and error. So, how do we teach an agent to play SS? Well, one way to do it would be to try to come up with a set of rules that we feed directly into the agent. The snake dies when it collides with the boundary wall or part of its own body. SS is a simple game where the snake tries to grow in length by eating more fruits. We do this by focusing on the goal of teaching an agent to play Screen-Snake (SS). Given the importance of these algorithms in our lives, sNNake is a project aimed at better understanding how reinforcement algorithms work. They are better than humans at Chess, Go, and driving. They help advertisers determine the optimal products to present us with. These algorithms suggest which Netflix shows we will like. BackgroundĮven if you are not interested in computer science, you have almost definitely interacted with reinforcement algorithms in your day-to-day life. Finally, this project provides a discussion on the ethical questions associated with the application of RL techniques across a wide range of fields and a reflection on the work conducted. After a brief introduction to RL concepts and related studies, it analyzes the performance of snake agents trained with different combinations of reinforcement algorithms and reward functions. This project explores the application of reinforcement learning (RL) algorithms to the well-known game screen snake. Link to presentation and demo - Link to slide deck - Link to raw experiment data - Link to repository Contents: Rect_middle = text.get_rect(center=((Game.WIDTH // 2, Game.SNNake: Reinforcement Learning Strategies in Screen Snake By Jack Weber, Dave Carroll, and David D’Attile Untrained sNNake
Game.write("Press s to start", middle="both")ĭef write(t, x: int = 0, y: int = 0, middle: str = "both", color="Coral") -> pygame.Surface: It is Game.screen, because screen is a variable of the class Game.
If you put middle=”both”, it will be centered on the Game.screen. In the write function you render the text, then you blit it on the Game.screen, on the surface and use () to show it. In the class Game you got some attributes that are useful, like the font that tells the computer to use arial characters of size 24. Rect_middle = text.get_rect(center=((Game.WIDTH // 2, Game.HEIGHT //2))) This is the function that makes you write “press s to start” def write(t, x: int = 0, y: int = 0, middle: str = "both", color="Coral") -> pygame.Surface:
#SCREEN SNAKE CODE#
The code is this for the input, the ‘s’ of course will do nothing but print start while True: We used this function to make the computer to wait for the input: event = () The possible inputs: quit, escape or ‘s’ to start This is done just to wait the user to press s without making the game start immediately. That is all we will have for this first part. You can find the whole code and the code of the different parts of the tutorial here in this GITHUB REPOSITORY (there is also a snake.7 version with the latest version with some sound adjustments). Now that I posted 3 version of snake ( Snake 1, Snake 2, Snake 3), let’s remake Snake from skratch.
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