Risk-Sensitive Reinforcement Learning via Policy Gradient Search L. a. Prashanth
Risk-Sensitive Reinforcement Learning via Policy Gradient Search L. a. Prashanth Reinforcement learning (RL) is one of the foundational pillars of artificial intelligence and machine learning. This…
Specifikacia Risk-Sensitive Reinforcement Learning via Policy Gradient Search L. a. Prashanth
Risk-Sensitive Reinforcement Learning via Policy Gradient Search L. a. Prashanth
Reinforcement learning (RL) is one of the foundational pillars of artificial intelligence and machine learning. This monograph surveys research on risk-sensitive RL that uses policy gradient search.The authors survey some of the recent work in this area specifically where policy gradient search is the solution approach. An important consideration in any optimization or control problem is the notion of risk, but its incorporation into RL has been a fairly recent development.
For the setting where risk is incorporated directly into the objective function, they consider an exponential utility formulation, cumulative prospect theory, In the first risk-sensitive RL setting, they cover popular risk measures based on variance, conditional value at-risk and chance constraints, and present a template for policy gradient-based risk-sensitive RL algorithms using a Lagrangian formulation.