A RL agent trained to play Mario using DDQN
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Updated
Jul 10, 2022 - Jupyter Notebook
A RL agent trained to play Mario using DDQN
q learning & deep q learning using pytorch
Ensuring trust among agents using Multi-Agent Deep Reinforcement Learning
Deep reinforcement nano degree in Udacity - Prioritized Double DQN
Reinforcement Learning
A repo contains my implementation and analysis of some well-known Reinforcement Learning problems and algorithms.
Reinforcement Learning Implementations in PyTorch
⛷ DQN and DDQN algorithms for OpenAI Gym Skiing environment 🎮
Implementation of a DDQN to play SMB for the NES.
Implementing deep reinforcement learning algorithm for banana collector and other upcoming project. Using different technique such as Deep Q-network (DQN) and Double Deep Quick Network (DDQN)
Tensorflow based DQN and PyTorch based DDQN Agent for 'MountainCar-v0' openai-gym environment.
Implementation and evaluation of the RL algorithm Rainbow to learn to play Atari games.
Reinforcement Learning Tutorials & other bedtime stories in PyTorch
In this repository, we try to solve musculoskeletal tasks with `Double DQN reinforcement learning` by using a `transformer` model has been used as the base model architecture.
This code is the result of the collaboration of RL Turkey team.
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
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