Description

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.

– 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/6lu0gTPYFzY

Technical Details

(Please include a full, comprehensive list of the features of the product)

Code Modules:

Number of Blueprints: 9

Number of C++ Classes: 1

Network Replicated: No

Supported Development Platforms: Windows

Documentation: https://github.com/Nullspace-Colombia/unray-bridge/tree/master

Important/Additional Notes: Unray plugin is complimented with a Python API counterpart, which makes use of RLLib, so it is necessary to install and develop the training from a Python IDE.

Supported Engine Versions

5.3