Thesis project: reinforcement learning environments for ai agents

Your thesis will connect to our ongoing work with Predli Studio and help shape how we design and evaluate AI agent behaviors in practice. This thesis will focus on the development of advanced RL scenarios that challenge agent adaptability, generalization and decision-making under uncertainty, providing valuable insights into the capabilities and limitations of current RL approaches.