40 citations · 58 across the 11 of their papers we have counts for
4 papers · 1 filter
Local Policy Optimization for Trajectory-Centric Reinforcement Learning
Patrik Kolaric, Devesh K. Jha, Arvind U. Raghunathan +4
The goal of this paper is to present a method for simultaneous trajectory and local stabilizing policy optimization to generate local policies for trajectory-centric model-based re…
Quasi-Newton Trust Region Policy Optimization
Devesh Jha, Arvind Raghunathan, Diego Romeres
We propose a trust region method for policy optimization that employs Quasi-Newton approximation for the Hessian, called Quasi-Newton Trust Region Policy Optimization QNTRPO. Gradi…
JANOS: An Integrated Predictive and Prescriptive Modeling Framework
David Bergman, Teng Huang, Philip Brooks +2
Business research practice is witnessing a surge in the integration of predictive modeling and prescriptive analysis. We describe a modeling framework JANOS that seamlessly integra…
Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function
Arvind U. Raghunathan, Anoop Cherian, Devesh K. Jha
Computing Nash equilibrium (NE) of multi-player games has witnessed renewed interest due to recent advances in generative adversarial networks. However, computing equilibrium effic…