MountainCar Deep-Q Network

MountainCar-v0 is a gym environment. Discretized continuous state space and solved using Q-learning.

opengym mountain car continuous model trained with actor critic method

Applied various Reinforcement Learning (RL) algorithms to determine the optimal policy for diverse Markov Decision Processes (MDPs) specified within the OpenAI Gym library

A solution for the MountainCar-v0 problem of the Gym environment

PGuNN - Playing Games using Neural Networks

Mountain Car is a Gym environment. I used this environment to train my model using Q-Learning which is a reinforcement learning technic.

This repo constains the implementation of REINFORCE and REINFORCE-Baseline algorithm on Mountain car problem.

Deep RL on OpenAI gym environment

Mountain car problem via Q-learning.

DQN Play Flappy-bird and MountainCar

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.

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

RL with OpenAI Gym