Search Results for author: Ryan Gardner

Found 2 papers, 0 papers with code

A Risk-Sensitive Policy Gradient Method

no code implementations29 Sep 2021 Jared Markowitz, Ryan Gardner, Ashley Llorens, Raman Arora, I-Jeng Wang

Standard deep reinforcement learning (DRL) agents aim to maximize expected reward, considering collected experiences equally in formulating a policy.

Decision Making

Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

no code implementations6 Nov 2018 Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan Gardner, Daniel Genin, Joshua Silbermann, Michael Owen, Mykel J. Kochenderfer

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars.

Autonomous Driving reinforcement-learning +1

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