Shypd.aiThe largest open index of AI toolsslimevolleygym is an OpenAI Gym environment for single and multi-agent reinforcement learning, simulating a simple Slime Volleyball game. It allows researchers to train AI agents efficiently with minimal dependencies.
Trending
About
slimevolleygym is an OpenAI Gym environment designed for testing single and multi-agent reinforcement learning algorithms through a simple Slime Volleyball game. This environment is lightweight, requiring only gym and numpy as dependencies, making it less prone to breaking and easy to integrate. It features a baseline 120-parameter neural network opponent, which can be replaced for multi-agent or self-play scenarios. The environment runs efficiently, achieving around 12.5K timesteps per second on state-space observations, facilitating faster iteration in experiments. It supports both state-space and pixel observations, with the latter mimicking Atari Learning Environment setups, and includes a tutorial for various training methods. The environment is particularly useful for educational purposes and for exploring advanced RL methods like self-play and continual learning.
Capabilities
Pricing & Plans
Open Source
Free
FAQs
Trending
Also listed in
.png&w=3840&q=75){kind=small}