Discover how Unray can power your game and simulation development with reinforcement learning in Unreal Engine:

1. Interactive Game Development: Use Unray to create complex game environments with multiple agents that learn and adapt as they play.

2. Realistic Environment Simulations: Create realistic simulations to train agents in environments that mimic real-world situations.

3. Research in Artificial Intelligence: Employ Unray as a research platform to experiment with different reinforcement learning algorithms in multi-agent environments.

Features:

- Uses powerful RLlib technology for effective training.

- Leverages the ability to parallelize training using Ray technology.

- Supports a variety of algorithms, including PPO, QMIX, DQN, in addition to those built into the RLLib library.

- Facilitates the creation of multi-agent environments.

Demo Video: https://youtu.be/byKlMvXkpfg

Discord Server: https://discord.com/invite/m4YXAhpdhS