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lunar-lander-game

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This project implements Deep Q-Network (DQN) and Double DQN from scratch using PyTorch to solve the Lunar Lander environment. The repository focuses on clean implementation, reproducible experiments, and performance comparison between both algorithms.

  • Updated Jul 18, 2026
  • Python

Landing pad is always at coordinates (0,0). Coordinates are the first two numbers in state vector. Reward for moving from the top of the screen to landing pad and zero speed is about 100..140 points. If lander moves away from landing pad it loses reward back. Episode finishes if the lander crashes or comes to rest, receiving additional -100 or +…

  • Updated Sep 22, 2020
  • Python

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