phillip
DI-sheep
phillip | DI-sheep | |
---|---|---|
2 | 1 | |
539 | 362 | |
- | 0.0% | |
0.0 | 10.0 | |
over 1 year ago | about 1 year ago | |
Python | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
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phillip
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[P] Imitation Learning (+RL) in Super Smash Bros Melee for Humanlike Agents
Project Nabla is an AI trained with deep neural networks using behavioral cloning and deep reinforcement learning self-play, similar to AlphaStar. It is enabled by the recent launch of a suite of software tools for the game known as "Slippi" which allow for us to save human replays. We train on a subset of ~100k tournament games. It is similar to the older Phillip project, which did not have the benefit of Slippi when it was created (and doesn't use any human replays).
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Imma write a machine learning program and let it run for a month
Could take a look at this https://github.com/vladfi1/phillip
DI-sheep
What are some alternatives?
habitat-api - A modular high-level library to train embodied AI agents across a variety of tasks, environments, and simulators. [Moved to: https://github.com/facebookresearch/habitat-lab]
PyGame-Learning-Environment - PyGame Learning Environment (PLE) -- Reinforcement Learning Environment in Python.
auction-app - A simple auction app built with React and Django.
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
habitat-lab - A modular high-level library to train embodied AI agents across a variety of tasks and environments.
deepdrive - Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving