Deep Q-Leaning trained to play Doom (openAI gym env)
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Updated
Feb 23, 2018 - Python
Deep Q-Leaning trained to play Doom (openAI gym env)
Research about applying reinforcement learning to realitic problems. Collects data then figure out how good reinforcement learning is.
Automated Car with Reinforcement Learning. Learning is done using penalty and rewards.
Naive Q-Learning approach to self-driving cars
Dots and Boxes with reinforcement lerning
The project implements a reinforcement learning agent that can play the Space Invaders Atari game. I compare the performance of the agent using Double Deep Q-Learning with simple Deep Q-Learning.
Implement Q-Learning and DQN algorithms to solve FrozenLake problem.
Just another approach to do machine learning stuff on games.
playing around with keras open ai and conv nets
Learning from AI
Q-Learning Algorithm to teach a taxi agent to navigate a small grid world
Training an agent to play game using reinforcement learning
OpenAI Gym reinforcement learning examples. FrozenLake-v0 and Taxi-v2
Machine learning algorithms
Implementation of REINFORCE for open ai env acrobot, epsilon greedy Q-Learning for open ai env taxi & TD(0) for custom gameshow env KBC.
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