Solving OpenAI Gym problems.
-
Updated
Jan 12, 2021 - Python
Solving OpenAI Gym problems.
Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM)
A simple baseline for mountain-car @ gym
Tensorflow based DQN and PyTorch based DDQN Agent for 'MountainCar-v0' openai-gym environment.
Solving MountainCar-v0 environment in Keras with Deep Q Learning an Deep Reinforcement Learning algorithm
OpenAI MountainCar-v0 DeepRL-based solutions (DQN, DuelingDQN, D3QN)
Deep RL agent for solving MountainCar-v0 environment.
An implementation of main reinforcement learning algorithms: solo-agent and ensembled versions.
Applied various Reinforcement Learning (RL) algorithms to determine the optimal policy for diverse Markov Decision Processes (MDPs) specified within the OpenAI Gym library
opengym mountain car continuous model trained with actor critic method
PGuNN - Playing Games using Neural Networks
A solution for the MountainCar-v0 problem of the Gym environment
Mountain Car is a Gym environment. I used this environment to train my model using Q-Learning which is a reinforcement learning technic.
Mountain car problem via Q-learning.
This repo constains the implementation of REINFORCE and REINFORCE-Baseline algorithm on Mountain car problem.
Deep RL on OpenAI gym environment
Add a description, image, and links to the mountaincar-v0 topic page so that developers can more easily learn about it.
To associate your repository with the mountaincar-v0 topic, visit your repo's landing page and select "manage topics."