There are 5 repositories under rl-agents topic.
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
Tensorflow 2 Reinforcement Learning Cookbook, published by Packt
Train a tic-tac-toe agent using reinforcement learning.
RL-Toolkit: A Research Framework for Robotics
Pytorch Implementation of RL algorithms
Boid flock multi-agent RL training environment
Pytorch Implementation of RL algorithms
dITC through RL Code Foundation
This project focuses on comparing different Reinforcement Learning Algorithms, including monte-carlo, q-learning, lambda q-learning epsilon-greedy variations, etc.
A reinforcement learning agent navigating the OpenAI's FrozenLake environment
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 generalized policy of playing the game. Our hypothesis is that training the agent with the additional levels will lead to an optimal policy that performs better than the policy learned from the few pre-existing levels. Our final objective is to learn such a generative model, train an RL agent with the generated levels and test its performance on a set of unseen game levels.
Collect more gift than an AI opponent in this fast-paced Christmas-themed game.
A general-purpose remote environment for training RL agents.
First version of social 2-step task with shocks.
Train a tic-tac-toe agent with reinforcement learning.
Some Reinforcement Learning in Python. Especially how to get the feature for linear function approximation.
This repo contains toy solutions for the openAI gym environment implementing Q-networks in Keras and TensorFlow
Open Gym Taxi v3 environment solved using sarsamax algorithm(Q-Learning)