Alternatives and similar repositories for snake-on-pygame

Users that are interested in snake-on-pygame are comparing it to the libraries listed below

• ZidanMusk / deep-RL-DQN-tensorflow
  TensorFlow implementation of Deep RL (Reinforcement Learning) papers based on deep Q-learning (DQN)
  ☆10Updated 7 years ago
• tobiassteidle / Reinforcement-Learning
  Solutions for different Reinforcement Learning environments
  ☆26Updated last year
• hope-yao / cartpole
  Tensorflow implementation of DQN to control cart-pole from OpenAI gym environment
  ☆14Updated 8 years ago
• davidreiman / pytorch-atari-dqn
  A PyTorch implementation of deep Q-learning for Atari games
  ☆14Updated 7 years ago
• hzm2016 / sources-of-reinforcement-learning
  All the source codes and lectures of reinforcement learning.
  ☆33Updated 5 years ago
• txzhao / rl-zoo
  PyTorch implementation of various reinforcement learning algorithms
  ☆18Updated 7 years ago
• artem-oppermann / Deep-Reinforcement-Learning
  A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
  ☆37Updated 5 years ago
• grantsrb / PyTorch-A2C
  General implementation of Advantage Actor Critic using Pytorch
  ☆28Updated 4 years ago
• jamesq9 / Tic-Tac-Toe-Machine-Learning-Using-Reinforcement-Learning
  A Python Program to implement Machine Learning for the Game Tic Tac Toe (3x3) using Reinforcement Learning (Q learning technique) and ten…
  ☆14Updated 8 years ago
• yunjhongwu / Double-DQN-Breakout
  Playing Breakout with double deep Q network
  ☆13Updated 8 years ago
• Meredevs / DQN_Pong
  My implementation of a deep q learning network learning to play pong.
  ☆10Updated 4 years ago
• zackchase / intrinsic-fear-dqn
  Avoiding catastrophic failures in reinforcement learning by learning to shape rewards.
  ☆10Updated 8 years ago
• ZainBashir / Solving-openAI-Gym-MountainCarProblem-using-DQN-with-Image-input
  I have targeted to solve the benchmark problem in Reinforcement learning literature using Deep Q-networks with images as the only input t…
  ☆12Updated 6 years ago
• ykteh93 / Deep_Reinforcement_Learning-Atari
  Deep Q-Network (DQN) to play classic Atari Games
  ☆11Updated 8 years ago
• veronicachelu / meta-learning
  Meta Reinforcement Learning Experiments
  ☆35Updated 8 years ago
• go2sea / NoisyNetDQN
  Tensorflow implementation for "Noisy network for exploration"
  ☆19Updated 8 years ago
• wotmd5731 / dqn
  pytorch, noisy_distributional_double_dueling_PER_RNN_CNN...CartPole-v1 , Acrobot-v1, MountainCar-v0
  ☆14Updated 7 years ago
• pucrs-ai-cs / reinforcement
  Reinforcement Learning
  ☆12Updated 8 years ago
• TomZahavy / GrayingTheBox
  Code implementation of: "Graying the black box: Understanding DQNs"
  ☆20Updated 8 years ago
• pikinder / DQN
  Deep Q-Networks in tensorflow
  ☆10Updated 8 years ago
• DragonWarrior15 / snake-rl
  Snake using RL
  ☆19Updated 2 years ago
• mmuppidi / DQN-Atari-Pong
  This project explores a deep reinforcement learning technique to train an agent to play atari pong game from OpenAI Gym. OpenAI Gym is a …
  ☆12Updated 7 years ago
• eunae-park / EdgeComputing_DataAggregator
  ☆17Updated last year
• bryonkucharski / Learning-to-Drive-with-Reinforcement-Learning-and-Variational-Autoencoders
  Project for my graduate neural networks course - combining RL with VAEs
  ☆23Updated 6 years ago
• moduIo / Deep-Q-network
  Keras implementation of DQN for the MsPacman-v0 OpenAI Gym environment.
  ☆37Updated 3 years ago
• GitScrider / FederatedEdgeComputing
  a Federated Learning Framework adapted for resource-constrained environments, focusing on IoT devices
  ☆10Updated 3 months ago
• benbotto / bsy-dqn-atari
  A DQN implementation using Keras and Tensorflow
  ☆12Updated 7 years ago
• ArztSamuel / DRL_DeliveryDuel
  Deep Reinforcement Learning applied to a modern 3D video-game environment called Delivery Duel.
  ☆41Updated 7 years ago
• yanpanlau / CartPole
  Various DQN method with cartpole
  ☆11Updated 7 years ago
• automl / learning_environments
  We propose an evolution-based approach to meta-learn synthetic neural environments and reward neural networks for reinforcement learning.
  ☆21Updated 2 years ago