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07/31/2023
Learning to Model the World with Language
To interact with humans in the world, agents need to understand the dive...
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07/27/2023
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback
Reinforcement learning from human feedback (RLHF) is a technique for tra...
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06/30/2023
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control
Our goal is for robots to follow natural language instructions like "put...
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06/14/2023
Toward Grounded Social Reasoning
Consider a robot tasked with tidying a desk with a meticulously construc...
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04/19/2023
Bridging RL Theory and Practice with the Effective Horizon
Deep reinforcement learning (RL) works impressively in some environments...
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03/08/2023
Automatically Auditing Large Language Models via Discrete Optimization
Auditing large language models for unexpected behaviors is critical to p...
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03/03/2023
Learning to Influence Human Behavior with Offline Reinforcement Learning
In the real world, some of the most complex settings for learned agents ...
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01/02/2023
Towards Modeling and Influencing the Dynamics of Human Learning
Humans have internal models of robots (like their physical capabilities)...
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12/09/2022
On the Sensitivity of Reward Inference to Misspecified Human Models
Inferring reward functions from human behavior is at the center of value...
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11/30/2022
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking
One of the most successful paradigms for reward learning uses human feed...
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11/20/2022
UniMASK: Unified Inference in Sequential Decision Problems
Randomly masking and predicting word tokens has been a successful approa...
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11/03/2022
Optimal Behavior Prior: Data-Efficient Human Models for Improved Human-AI Collaboration
AI agents designed to collaborate with people benefit from models that e...
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04/28/2022
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers
Randomly masking and predicting word tokens has been a successful approa...
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04/25/2022
Estimating and Penalizing Induced Preference Shifts in Recommender Systems
The content that a recommender system (RS) shows to users influences the...
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04/22/2022
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models
Models of human behavior for prediction and collaboration tend to fall i...
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04/05/2022
Inferring Rewards from Language in Context
In classic instruction following, language like "I'd like the JetBlue fl...
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11/12/2021
Human irrationality: both bad and good for reward inference
Assuming humans are (approximately) rational enables robots to infer rew...
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11/04/2021
B-Pref: Benchmarking Preference-Based Reinforcement Learning
Reinforcement learning (RL) requires access to a reward function that in...
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07/05/2021
The MineRL BASALT Competition on Learning from Human Feedback
The last decade has seen a significant increase of interest in deep lear...
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04/08/2021
Learning What To Do by Simulating the Past
Since reward functions are hard to specify, recent work has focused on l...
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01/19/2021
Choice Set Misspecification in Reward Inference
Specifying reward functions for robots that operate in environments with...
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06/26/2020
AvE: Assistance via Empowerment
One difficulty in using artificial agents for human-assistive applicatio...
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10/13/2019
On the Utility of Learning about Humans for Human-AI Coordination
While we would like agents that can coordinate with humans, current algo...
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02/12/2019
Preferences Implicit in the State of the World
Reinforcement learning (RL) agents optimize only the features specified ...
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01/24/2019
The Assistive Multi-Armed Bandit
Learning preferences implicit in the choices humans make is a well studi...
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01/04/2019
On the Utility of Model Learning in HRI
Fundamental to robotics is the debate between model-based and model-free...
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05/31/2018
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning
A significant challenge for the practical application of reinforcement l...
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02/06/2018
Shared Autonomy via Deep Reinforcement Learning
In shared autonomy, user input is combined with semi-autonomous control ...
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11/08/2017
Inverse Reward Design
Autonomous agents optimize the reward function we give them. What they d...
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05/28/2017
Should Robots be Obedient?
Intuitively, obedience -- following the order that a human gives -- seem...
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04/23/2017
Translating Neuralese
Several approaches have recently been proposed for learning decentralize...
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11/24/2016
The Off-Switch Game
It is clear that one of the primary tools we can use to mitigate the pot...
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06/09/2016