Stuart Russell

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 50

Top Topics

Nash Equilibria

Reinforcement Learning

Reward Function

Top Venues

Publications

Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan
AI Alignment with Changing and Influenceable Reward Functions. CoRR (2024)
Erik Jenner, Shreyas Kapur, Vasil Georgiev, Cameron Allen, Scott Emmons, Stuart Russell
Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. CoRR (2024)
Hanlin Zhu, Baihe Huang, Shaolun Zhang, Michael I. Jordan, Jiantao Jiao, Yuandong Tian, Stuart Russell
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. CoRR (2024)
Qingyuan Lu, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein, Stuart Russell
Ethically Compliant Autonomous Systems under Partial Observability. ICRA (2024)
Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell
Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. ICLR (2024)
Hanlin Zhu, Baihe Huang, Stuart Russell
On Representation Complexity of Model-based and Model-free Reinforcement Learning. ICLR (2024)
Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. ICLR (2024)
Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker
Social Choice for AI Alignment: Dealing with Diverse Human Feedback. CoRR (2024)
Shreyas Kapur, Erik Jenner, Stuart Russell
Diffusion On Syntax Trees For Program Synthesis. CoRR (2024)
David Dalrymple, Joar Skalse, Yoshua Bengio, Stuart Russell, Max Tegmark, Sanjit Seshia, Steve Omohundro, Christian Szegedy, Ben Goldhaber, Nora Ammann, Alessandro Abate, Joe Halpern, Clark W. Barrett, Ding Zhao, Tan Zhi-Xuan, Jeannette Wing, Joshua B. Tenenbaum
Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. CoRR (2024)
Benjamin Plaut, Hanlin Zhu, Stuart Russell
Avoiding Catastrophe in Continuous Spaces by Asking for Help. CoRR (2024)
Leon Lang, Davis Foote, Stuart Russell, Anca D. Dragan, Erik Jenner, Scott Emmons
When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning. CoRR (2024)
Andrew Critch, Stuart Russell
TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI. CoRR (2023)
Tony Tong Wang, Adam Gleave, Tom Tseng, Kellin Pelrine, Nora Belrose, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell
Adversarial Policies Beat Superhuman Go AIs. ICML (2023)
Peter Barnett, Rachel Freedman, Justin Svegliato, Stuart Russell
Active Reward Learning from Multiple Teachers. SafeAI@AAAI (2023)
Edmund Mills, Shiye Su, Stuart Russell, Scott Emmons
ALMANACS: A Simulatability Benchmark for Language Model Explainability. CoRR (2023)
Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael D. Dennis, Stuart Russell
Who Needs to Know? Minimal Knowledge for Optimal Coordination. ICML (2023)
Rachel Freedman, Justin Svegliato, Kyle Hollins Wray, Stuart Russell
Active teacher selection for reinforcement learning from human feedback. CoRR (2023)
Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann
Managing AI Risks in an Era of Rapid Progress. CoRR (2023)
Alistair Knott, Dino Pedreschi, Raja Chatila, Tapabrata Chakraborti, Susan Leavy, Ricardo Baeza-Yates, David M. Eyers, Andrew Trotman, Paul D. Teal, Przemyslaw Biecek, Stuart Russell, Yoshua Bengio
Generative AI models should include detection mechanisms as a condition for public release. Ethics Inf. Technol. 25 (4) (2023)
Mason Nakamura, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein, Stuart Russell
Formal Composition of Robotic Systems as Contract Programs. IROS (2023)
Joar Max Viktor Skalse, Matthew Farrugia-Roberts, Stuart Russell, Alessandro Abate, Adam Gleave
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. ICML (2023)
Luke Bailey, Euan Ong, Stuart Russell, Scott Emmons
Image Hijacks: Adversarial Images can Control Generative Models at Runtime. CoRR (2023)
Peter Barnett, Rachel Freedman, Justin Svegliato, Stuart Russell
Active Reward Learning from Multiple Teachers. CoRR (2023)
Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. CoRR (2023)
Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka
SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals. AISTATS (2023)
Sam Toyer, Olivia Watkins, Ethan Adrian Mendes, Justin Svegliato, Luke Bailey, Tiffany Wang, Isaac Ong, Karim Elmaaroufi, Pieter Abbeel, Trevor Darrell, Alan Ritter, Stuart Russell
Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. CoRR (2023)
Cassidy Laidlaw, Stuart Russell, Anca D. Dragan
Bridging RL Theory and Practice with the Effective Horizon. CoRR (2023)
Hanlin Zhu, Baihe Huang, Stuart Russell
On Representation Complexity of Model-based and Model-free Reinforcement Learning. CoRR (2023)
Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian. ICLR (2023)
Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael Dennis, Stuart Russell
Who Needs to Know? Minimal Knowledge for Optimal Coordination. CoRR (2023)
Micah D. Carroll, Anca D. Dragan, Stuart Russell, Dylan Hadfield-Menell
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. ICML (2022)
Tony Tong Wang, Adam Gleave, Nora Belrose, Tom Tseng, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell
Adversarial Policies Beat Professional-Level Go AIs. CoRR (2022)
Scott Emmons, Caspar Oesterheld, Andrew Critch, Vincent Conitzer, Stuart Russell
For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria. CoRR (2022)
Joar Skalse, Matthew Farrugia-Roberts, Stuart Russell, Alessandro Abate, Adam Gleave
Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. CoRR (2022)
Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. CoRR (2022)
Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
An Empirical Investigation of Representation Learning for Imitation. CoRR (2022)
Arnaud Fickinger, Samuel Cohen, Stuart Russell, Brandon Amos
Cross-Domain Imitation Learning via Optimal Transport. ICLR (2022)
Scott Emmons, Caspar Oesterheld, Andrew Critch, Vincent Conitzer, Stuart Russell
For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria. ICML (2022)
Samer B. Nashed, Justin Svegliato, Abhinav Bhatia, Stuart Russell, Shlomo Zilberstein
Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning. IROS (2022)
Andrew Critch, Michael Dennis, Stuart Russell
Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory. CoRR (2022)
Stuart Russell
Provably Beneficial Artificial Intelligence. IUI (2022)
Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian. CoRR (2022)
Adam Gleave, Mohammad Taufeeque, Juan Rocamonde, Erik Jenner, Steven H. Wang, Sam Toyer, Maximilian Ernestus, Nora Belrose, Scott Emmons, Stuart Russell
imitation: Clean Imitation Learning Implementations. CoRR (2022)
Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. IEEE Trans. Inf. Theory 68 (12) (2022)
Kenji Doya, Arisa Ema, Hiroaki Kitano, Masamichi Sakagami, Stuart Russell
Social impact and governance of AI and neurotechnologies. Neural Networks 152 (2022)
Cassidy Laidlaw, Stuart Russell
Uncertain Decisions Facilitate Better Preference Learning. NeurIPS (2021)
Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, Stuart Russell
MADE: Exploration via Maximizing Deviation from Explored Regions. NeurIPS (2021)
Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. NeurIPS (2021)
Cynthia Chen, Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H. Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah
An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks (2021)
Siddharth Srivastava, Stuart Russell, Avi Pfeffer
First-Order Models for POMDPs. StarAI@UAI (2012)