Scaling In-Context Reinforcement Learning: Empowering Generalist AI Agents for Enhanced Decision-Making and Adaptability
In-Context Reinforcement Learning (ICRL) is a method that allows AI systems to learn and adapt while interacting with their environments. However, it struggles with complex tasks due to challenges in generalizing past experiences. Researchers from Dunnolab AI have introduced Vintix, an innovative model that uses Algorithm Distillation to enhance ICRL. Vintix employs a transformer architecture ...
