Solving OpenAI Gym problems.

Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM)

OpenAI MountainCar-v0 DeepRL-based solutions (DQN, DuelingDQN, D3QN)

An implementation of main reinforcement learning algorithms: solo-agent and ensembled versions.

A simple baseline for mountain-car @ gym

Solving MountainCar-v0 environment in Keras with Deep Q Learning an Deep Reinforcement Learning algorithm

RL with OpenAI Gym

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

DQN Play Flappy-bird and MountainCar

Tensorflow based DQN and PyTorch based DDQN Agent for 'MountainCar-v0' openai-gym environment.

Application of Reinforcement Learning algorithms (DQN,DRQN,PPO,A2C) to gym's MountainCar-v0

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

Deep RL on OpenAI gym environment

Deep RL agent for solving MountainCar-v0 environment.

PGuNN - Playing Games using Neural Networks

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

Mountain car problem via Q-learning.

Reinforcement learning solution for the Mountain Car problem using value iteration, policy iteration, and Q-learning in OpenAI Gym.

Project of COMP4125 in 2024-2025.