2048 environment for Reinforcement Learning and DQN algorithm
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Updated
May 27, 2022 - Python
2048 environment for Reinforcement Learning and DQN algorithm
Deep Reinforcement Learning with Double Q-learning
This is an implementation of Deep Reinforcement Learning for a navigation task. Specifically, DQN algorithm with experience replay method is used to solve the task.
This repo hosts a sophisticated reinforcement learning setup for training a DQN agent in “CarRacing-v2”. It has self-adaptive features like dynamic learning rate and domain randomization to boost agent training and performance. It includes an Evaluation Callback for optimal model retention and leverages GPU for quicker training.
Simple breakout game with DQN agent which learn how to play it.
a 2D platformer game made with Unity engine and C#
Reinforcement Learning: Cartpole Balancing with a DQN Agent
Implementations of some of the most well known Deep Reinforcement Learning algorithms
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