Risk-Averse Control of Markov Systems
摘要
This chapter is devoted to dynamic risk measurement and risk-averse control in discrete-time systems described by controlled Markov kernels. The main idea of our approach is to exploit the structure of the canonical probability space to represent conditional risk measures by simpler structures, called transition risk mappings, which evaluate the risk of a function of the system’s state.