It is a multi-agent simulation library in Python designed to simulate and optimize systems and environments where multiple agents interact. The library, named Westworld, is inspired by Unity software and Unity ML Agents, and its primary goal is to facilitate simulations in fields such as logistics, retail, and epidemiology. It provides pre-coded spatial environments and enables communication between agents, with optimization capabilities using heuristics and Reinforcement Learning.
Westworld is currently in an experimental phase, marked as an alpha-release, and is under active development. As a result, users should not expect fully up-to-date documentation or thoroughly tested features. The library’s name is inspired by the TV series “Westworld,” which depicts a large-scale multi-agent simulation system. Documentation is available locally in the `docs` folder or online at [https://theolvs.github.io/westworld](https://theolvs.github.io/westworld). The library can be installed via PyPi, and a JavaScript version is also in development at [https://github.com/TheoLvs/westworldjs](https://github.com/TheoLvs/westworldjs).
The repository includes features such as pre-coded environments, agent communication, and optimization tools, with a roadmap for future enhancements. Users are encouraged to provide feedback, as the developers actively read and take input seriously. The project is open-source, with contributions welcomed, and is licensed under an unspecified license. The repository is maintained by two contributors and includes resources for installation, development, and further exploration of its capabilities.
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