4 papers
Optimized Certainty Equivalent Risk Minimization Using Samples: Algorithms, Convergence Rates, and Applications
Sumedh Gupte, Prashanth L. A., Sanjay P. Bhat
We consider the optimization of the Optimized Certainty Equivalent (OCE) risk, with applications including portfolio optimization in finance, and uncertainty quantification, classi…
Finite-Time Analysis of Discounted Exponential-Utility Reinforcement Learning
Ankur Naskar, Vivek T A, Aditya Kumar +2
Discounted exponential utility provides a principled criterion for risk-sensitive sequential decision-making, but its nonlinear structure complicates reinforcement learning. A rece…
Reinforcement Learning for Exponential Utility: Algorithms and Convergence in Discounted MDPs
Gugan Thoppe, L. A. Prashanth, Ankur Naskar +1
Reinforcement learning (RL) for exponential-utility optimization in discounted Markov decision processes (MDPs) lacks principled value-based algorithms. We address this gap in the…
Risk-sensitive reinforcement learning using expectiles, shortfall risk and optimized certainty equivalent risk
Sumedh Gupte, Shrey Rakeshkumar Patel, Soumen Pachal +2
We propose risk-sensitive reinforcement learning algorithms catering to three families of risk measures, namely expectiles, utility-based shortfall risk and optimized certainty equ…