Distributional Reinforcement Learning for Risk-Sensitive Sequential Decision Making: New Theory and Methods

Many critical online decision systems, including clinical support, financial risk management, and autonomous technologies, must look beyond average performance to avoid rare but catastrophic "tail events." Traditional reinforcement learning often summarizes future outcomes as a single expected value, which masks significant risks and uncertainty.…