In this project, we will produce a new framework for multi-agent AI systems that aims to advance the field of multi-agent learning and inform the development of GoodAI’s own artificial intelligence framework, Badger architecture. It will do so by both increasing our understanding of existing algorithms and how they can be applied and by the development of novel methods.
This project will focus on four areas where current artificial intelligence methods fall short:
1. The ability to have multiple, often competing goals
2. Coordination and communication from an information-theoretic perspective
3. Dynamic scalability of multi-agent systems
4. Dynamically changing goals that depend on knowledge acquired through observations