Pinned Repositories
CoRL
The Core Reinforcement Learning library is intended to enable scalable deep reinforcement learning experimentation in a manner extensible to new simulations and new ways for the learning agents to interact with them. The hope is that this makes RL research easier by removing lock-in to particular simulations.The work is released under the follow APRS approval. Initial release of CoRL - Part #1 -Approved on 2022-05-2024 12:08:51 - PA Approval # [AFRL-2022-2455]" Documentation https://act3-ace.github.io/CoRL/
browser-samples
Web samples for Google Workspace APIs
CommNet
Neural network model, suitable for multi-agent learning. https://arxiv.org/abs/1605.07736
MazeBase
Simple environment for creating very simple 2D games and training neural network models to perform tasks within them
reinforcement-learning
Minimal and Clean Reinforcement Learning Examples
hsclouse's Repositories
hsclouse/MazeBase
Simple environment for creating very simple 2D games and training neural network models to perform tasks within them
hsclouse/browser-samples
Web samples for Google Workspace APIs
hsclouse/CommNet
Neural network model, suitable for multi-agent learning. https://arxiv.org/abs/1605.07736
hsclouse/reinforcement-learning
Minimal and Clean Reinforcement Learning Examples