Reasoning about Counterfactuals to Improve Human Inverse Reinforcement
Learning

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Reasoning about Counterfactuals to Improve Human Inverse Reinforcement Learning

3 March 2022

Reid G. Simmons

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Papers citing "Reasoning about Counterfactuals to Improve Human Inverse Reinforcement Learning"

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Title
Explaining Reward Functions to Humans for Better Human-Robot Collaboration Lindsay M. Sanneman J. Shah 30 5 0 08 Oct 2021
Tradeoff-Focused Contrastive Explanation for MDP Planning Roykrong Sukkerd R. Simmons David Garlan 66 27 0 27 Apr 2020
Exploring Computational User Models for Agent Policy Summarization Isaac Lage Daphna Lifschitz Finale Doshi-Velez Ofra Amir LLMAG 65 76 0 30 May 2019
Establishing Appropriate Trust via Critical States Sandy H. Huang Kush S. Bhatia Pieter Abbeel Anca Dragan OffRL 70 111 0 18 Oct 2018
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications Daniel S. Brown S. Niekum OffRL 64 82 0 20 May 2018
An Overview of Machine Teaching Xiaojin Zhu Adish Singla Sandra Zilles Anna N. Rafferty 79 178 0 18 Jan 2018
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 250 4,273 0 22 Jun 2017
Enabling Robots to Communicate their Objectives Sandy H. Huang David Held Pieter Abbeel Anca Dragan 69 161 0 11 Feb 2017