An implementation of the neuroevolution algorithm NEAT
-
Updated
Apr 20, 2017 - Python
An implementation of the neuroevolution algorithm NEAT
This project used the openai gym environment to train a neural network for playing openai games
OpenAI Gym Environment for Low-Latency Trading
💥💥 This is a easy installable extension for OpenAi Gym Environment. This simulates SpaceX Falcon landing.
solution to mountain car problem of OpenAI Gym
Master Thesis: Limit order placement with Reinforcement Learning
Gambler's problem environment implemented OpenAI gym-style
OpenAI Gym environment for Half Field Offense
OpenAI Gym environment for Platform
OpenAI Gym environment for Robot Soccer Goal
OpenAI Gym Environment for Quadrotors
DeepDip, a DRL Gym agent that plays no-press Diplomacy in BANDANA
Teaching a neural network how to write letters and digits with reinforcement learning.
Custom environment for OpenAI gym
TicTacToe trained using OpenAI
A gym environment for Connect4 including graphics.
Configurable Curriculum Learning Domain for Reinforcement Learning Agents. As specified by [Narvekar, Sanmit, Jivko Sinapov, and Peter Stone. "Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning." IJCAI. 2017.]
An OpenAI gym environment designed for the control of dynamical systems
This github contains a simple OpenAi Gym Maze Enviroment and (at now) a RL Algorithm to solve it.
Add a description, image, and links to the openai-gym-environment topic page so that developers can more easily learn about it.
To associate your repository with the openai-gym-environment topic, visit your repo's landing page and select "manage topics."