Nathan Lambert | DeepAI

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∙ 08/01/2023

Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings

Foundation models could eventually introduce several pathways for underm...

0 Sarah Shoker, et al. ∙

∙ 12/09/2022

Measuring Data

We identify the task of measuring data to quantitatively characterize th...

0 Margaret Mitchell, et al. ∙

∙ 04/22/2022

Reward Reports for Reinforcement Learning

The desire to build good systems in the face of complex societal effects...

0 Thomas Krendl Gilbert, et al. ∙

∙ 03/17/2022

Investigating Compounding Prediction Errors in Learned Dynamics Models

Accurately predicting the consequences of agents' actions is a key prere...

0 Nathan Lambert, et al. ∙

∙ 02/11/2022

Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems

In the long term, reinforcement learning (RL) is considered by many AI t...

9 Thomas Krendl Gilbert, et al. ∙

∙ 01/27/2022

The Challenges of Exploration for Offline Reinforcement Learning

Offline Reinforcement Learning (ORL) enablesus to separately study the t...

0 Nathan Lambert, et al. ∙

∙ 08/31/2021

BotNet: A Simulator for Studying the Effects of Accurate Communication Models on Multi-agent and Swarm Control

Decentralized control in multi-robot systems is dependent on accurate an...

0 Mark Selden, et al. ∙

∙ 04/26/2021

Axes for Sociotechnical Inquiry in AI Research

The development of artificial intelligence (AI) technologies has far exc...

0 Sarah Dean, et al. ∙

∙ 02/26/2021

On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning

Model-based Reinforcement Learning (MBRL) is a promising framework for l...

0 Baohe Zhang, et al. ∙

∙ 02/04/2021

AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks

Despite interest in communicating ethical problems and social contexts w...

0 McKane Andrus, et al. ∙

∙ 09/02/2020

Nonholonomic Yaw Control of an Underactuated Flying Robot with Model-based Reinforcement Learning

Nonholonomic control is a candidate to control nonlinear systems with pa...

0 Nathan Lambert, et al. ∙

∙ 02/11/2020

Objective Mismatch in Model-based Reinforcement Learning

Model-based reinforcement learning (MBRL) has been shown to be a powerfu...

0 Nathan Lambert, et al. ∙

∙ 09/26/2019

Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning

Learning to locomote to arbitrary goals on hardware remains a challengin...

0 Tianyu Li, et al. ∙

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