RL Agents for various OpenAI Gym environments
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Updated
Jan 18, 2017 - Python
RL Agents for various OpenAI Gym environments
This repo contains toy solutions for the openAI gym environment implementing Q-networks in Keras and TensorFlow
Some Reinforcement Learning in Python. Especially how to get the feature for linear function approximation.
A general-purpose remote environment for training RL agents.
Custom Reinforcement Learning Agents
This project focuses on comparing different Reinforcement Learning Algorithms, including monte-carlo, q-learning, lambda q-learning epsilon-greedy variations, etc.
Our project focuses on the problem of generating synthetic levels of a game such that the levels can be used to learn an optimal policy for playing the game. Given a few pre-existing game levels we want to use deep generative models (like GANs) to generate new additional game levels. We will then train an RL agent on these levels to learn a gene…
dITC through RL Code Foundation
Pytorch Implementation of RL algorithms
Implementation of Continuous Control RL Algorithms
Pytorch Implementation of RL algorithms
RL-Toolkit: A Research Framework for Robotics
Train a tic-tac-toe agent using reinforcement learning.
NLPGym - A toolkit to develop RL agents to solve NLP tasks.
Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa
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