| 2025 | AAAI | The Partially Observable Off-Switch Game. | Andrew Garber, Rohan Subramani, Linus Luu, Mark Bedaywi, Stuart Russell, Scott Emmons |
| 2025 | ICLR | Monitoring Latent World States in Language Models with Propositional Probes. | Jiahai Feng, Stuart Russell, Jacob Steinhardt |
| 2025 | ICLR | Diffusion On Syntax Trees For Program Synthesis. | Shreyas Kapur, Erik Jenner, Stuart Russell |
| 2025 | ICLR | BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping. | Aly Lidayan, Michael D. Dennis, Stuart Russell |
| 2025 | ICML | Observation Interference in Partially Observable Assistance Games. | Scott Emmons, Caspar Oesterheld, Vincent Conitzer, Stuart Russell |
| 2025 | ICML | Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts. | Jiahai Feng, Stuart Russell, Jacob Steinhardt |
| 2025 | ICML | AssistanceZero: Scalably Solving Assistance Games. | Cassidy Laidlaw, Eli Bronstein, Timothy Guo, Dylan Feng, Lukas Berglund, Justin Svegliato, Stuart Russell, Anca D. Dragan |
| 2025 | ICML | Avoiding Catastrophe in Online Learning by Asking for Help. | Benjamin Plaut, Hanlin Zhu, Stuart Russell |
| 2025 | UAI | RL, but don't do anything I wouldn't do. | Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell |
| 2024 | CoRL | Trajectory Improvement and Reward Learning from Comparative Language Feedback. | Zhaojing Yang, Miru Jun, Jeremy Tien, Stuart Russell, Anca D. Dragan, Erdem Biyik |
| 2024 | ICLR | The Effective Horizon Explains Deep RL Performance in Stochastic Environments. | Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan |
| 2024 | ICLR | Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game. | 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 |
| 2024 | ICLR | On Representation Complexity of Model-based and Model-free Reinforcement Learning. | Hanlin Zhu, Baihe Huang, Stuart Russell |
| 2024 | ICML | Image Hijacks: Adversarial Images can Control Generative Models at Runtime. | Luke Bailey, Euan Ong, Stuart Russell, Scott Emmons |
| 2024 | ICML | AI Alignment with Changing and Influenceable Reward Functions. | Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan |
| 2024 | ICML | Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback. | Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Moss, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker |
| 2024 | ICRA | Ethically Compliant Autonomous Systems under Partial Observability. | Qingyuan Lu, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein, Stuart Russell |
| 2023 | AAAI | Active Reward Learning from Multiple Teachers. | Peter Barnett, Rachel Freedman, Justin Svegliato, Stuart Russell |
| 2023 | AISTATS | SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals. | Alexander K. Lew, George Matheos, Tan Zhi-Xuan, Matin Ghavamizadeh, Nishad Gothoskar, Stuart Russell, Vikash K. Mansinghka |
| 2023 | ICLR | Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian. | Paria Rashidinejad, Hanlin Zhu, Kunhe Yang, Stuart Russell, Jiantao Jiao |
| 2023 | ICML | Who Needs to Know? Minimal Knowledge for Optimal Coordination. | Niklas Lauffer, Ameesh Shah, Micah Carroll, Michael D. Dennis, Stuart Russell |
| 2023 | ICML | Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. | Joar Max Viktor Skalse, Matthew Farrugia-Roberts, Stuart Russell, Alessandro Abate, Adam Gleave |
| 2023 | ICML | Adversarial Policies Beat Superhuman Go AIs. | Tony Tong Wang, Adam Gleave, Tom Tseng, Kellin Pelrine, Nora Belrose, Joseph Miller, Michael D. Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell |
| 2023 | IROS | Formal Composition of Robotic Systems as Contract Programs. | Mason Nakamura, Justin Svegliato, Samer B. Nashed, Shlomo Zilberstein, Stuart Russell |
| 2022 | ICLR | Cross-Domain Imitation Learning via Optimal Transport. | Arnaud Fickinger, Samuel Cohen, Stuart Russell, Brandon Amos |
| 2022 | ICML | Estimating and Penalizing Induced Preference Shifts in Recommender Systems. | Micah D. Carroll, Anca D. Dragan, Stuart Russell, Dylan Hadfield-Menell |
| 2022 | ICML | For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria. | Scott Emmons, Caspar Oesterheld, Andrew Critch, Vincent Conitzer, Stuart Russell |
| 2022 | IROS | Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning. | Samer B. Nashed, Justin Svegliato, Abhinav Bhatia, Stuart Russell, Shlomo Zilberstein |
| 2022 | IUI | Provably Beneficial Artificial Intelligence. | Stuart Russell |
| 2021 | ICLR | Quantifying Differences in Reward Functions. | Adam Gleave, Michael Dennis, Shane Legg, Stuart Russell, Jan Leike |
| 2021 | RecSys | Estimating and Penalizing Preference Shift in Recommender Systems. | Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan |
| 2020 | ICLR | Adversarial Policies: Attacking Deep Reinforcement Learning. | Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell |
| 2019 | AAAI | Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient. | Shihui Li, Yi Wu, Xinyue Cui, Honghua Dong, Fei Fang, Stuart Russell |
| 2019 | ICCV | Bayesian Relational Memory for Semantic Visual Navigation. | Yi Wu, Yuxin Wu, Aviv Tamar, Stuart Russell, Georgia Gkioxari, Yuandong Tian |
| 2018 | ICML | An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning. | Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan |
| 2018 | ICML | Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms. | Yi Wu, Siddharth Srivastava, Nicholas Hay, Simon S. Du, Stuart Russell |
| 2017 | AAAI | A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models. | Yusuf Bugra Erol, Yi Wu, Lei Li, Stuart Russell |
| 2017 | AAAI | The Off-Switch Game. | Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell |
| 2017 | AISTATS | Signal-based Bayesian Seismic Monitoring. | David A. Moore, Stuart Russell |
| 2017 | EMNLP | Adversarial Training for Relation Extraction. | Yi Wu, David Bamman, Stuart Russell |
| 2017 | IJCAI | Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions. | Aijun Bai, Stuart Russell |
| 2017 | IJCAI | The Off-Switch Game. | Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell |
| 2017 | IJCAI | Should Robots be Obedient? | Smitha Milli, Dylan Hadfield-Menell, Anca D. Dragan, Stuart Russell |
| 2017 | RoboCup | Concurrent Hierarchical Reinforcement Learning for RoboCup Keepaway. | Aijun Bai, Stuart Russell, Xiaoping Chen |
| 2016 | AAAI | Metaphysics of Planning Domain Descriptions. | Siddharth Srivastava, Stuart Russell, Alessandro Pinto |
| 2016 | IJCAI | Markovian State and Action Abstractions for MDPs via Hierarchical MCTS. | Aijun Bai, Siddharth Srivastava, Stuart Russell |
| 2016 | IJCAI | Swift: Compiled Inference for Probabilistic Programming Languages. | Yi Wu, Lei Li, Stuart Russell, Rastislav Bodk |
| 2016 | IROS | Sequential quadratic programming for task plan optimization. | Dylan Hadfield-Menell, Christopher Lin, Rohan Chitnis, Stuart Russell, Pieter Abbeel |
| 2015 | AAAI | Tractability of Planning with Loops. | Siddharth Srivastava, Shlomo Zilberstein, Abhishek Gupta, Pieter Abbeel, Stuart Russell |
| 2015 | UAI | Multitasking: Optimal Planning for Bandit Superprocesses. | Dylan Hadfield-Menell, Stuart Russell |
| 2015 | UAI | A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC. | Wei Wang, Stuart Russell |
| 2014 | IPMU | Unifying Logic and Probability: A New Dawn for AI? | Stuart Russell |
| 2014 | ICRA | Combined task and motion planning through an extensible planner-independent interface layer. | Siddharth Srivastava, Eugene Fang, Lorenzo Riano, Rohan Chitnis, Stuart Russell, Pieter Abbeel |
| 2014 | UAI | Fast Gaussian Process Posteriors with Product Trees. | David A. Moore, Stuart Russell |
| 2014 | UAI | First-Order Open-Universe POMDPs. | Siddharth Srivastava, Stuart Russell, Paul Ruan, Xiang Cheng |
| 2013 | AISTATS | Dynamic Scaled Sampling for Deterministic Constraints. | Lei Li, Bharath Ramsundar, Stuart Russell |
| 2013 | CHI | Writing and sketching in the air, recognizing and controlling on the fly. | Sharad Vikram, Lei Li, Stuart Russell |
| 2013 | ICML | The Extended Parameter Filter. | Yusuf Erol, Lei Li, Bharath Ramsundar, Stuart Russell |
| 2013 | UAI | Product Trees for Gaussian Process Covariance in Sublinear Time. | David A. Moore, Stuart Russell |
| 2012 | UAI | Selecting Computations: Theory and Applications. | Nicholas Hay, Stuart Russell, David Tolpin, Solomon Eyal Shimony |
| 2011 | AAAI | Global Seismic Monitoring: A Bayesian Approach. | Nimar S. Arora, Stuart Russell, Paul Kidwell, Erik B. Sudderth |
| 2011 | EDM | Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System. | Emma Brunskill, Stuart Russell |
| 2011 | IJCAI | Bounded Intention Planning. | Jason Andrew Wolfe, Stuart Russell |
| 2011 | UAI | A temporally abstracted Viterbi algorithm. | Shaunak Chatterjee, Stuart Russell |
| 2010 | AAAI | Automatic Inference in BLOG. | Nimar S. Arora, Stuart Russell, Erik B. Sudderth |
| 2010 | AAAI | Hierarchical Planning for Mobile Manipulation. | Jason Andrew Wolfe, Bhaskara Marthi, Stuart Russell |
| 2010 | UAI | Gibbs Sampling in Open-Universe Stochastic Languages. | Nimar S. Arora, Rodrigo de Salvo Braz, Erik B. Sudderth, Stuart Russell |
| 2010 | UAI | RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains. | Emma Brunskill, Stuart Russell |
| 2008 | UAI | Improving Gradient Estimation by Incorporating Sensor Data. | Gregory Lawrence, Stuart Russell |
| 2006 | ILP | First-Order Probabilistic Languages: Into the Unknown. | Brian Milch, Stuart Russell |
| 2006 | UAI | A Compact, Hierarchical Q-function Decomposition. | Bhaskara Marthi, Stuart Russell, David Andre |
| 2006 | UAI | General-Purpose MCMC Inference over Relational Structures. | Brian Milch, Stuart Russell |
| 2005 | AISTATS | Approximate Inference for Infinite Contingent Bayesian Networks. | Brian Milch, Bhaskara Marthi, David A. Sontag, Stuart Russell, Daniel L. Ong, Andrey Kolobov |
| 2005 | IJCAI | Concurrent Hierarchical Reinforcement Learning. | Bhaskara Marthi, Stuart Russell, David Latham, Carlos Guestrin |
| 2005 | IJCAI | BLOG: Probabilistic Models with Unknown Objects. | Brian Milch, Bhaskara Marthi, Stuart Russell, David A. Sontag, Daniel L. Ong, Andrey Kolobov |
| 2005 | IJCAI | Efficient belief-state AND-OR search, with application to Kriegspiel. | Stuart Russell, Jason Andrew Wolfe |
| 2003 | ICML | Q-Decomposition for Reinforcement Learning Agents. | Stuart Russell, Andrew Zimdars |
| 2003 | IJCAI | Logical Filtering. | Eyal Amir, Stuart Russell |
| 2003 | UAI | Efficient Gradient Estimation for Motor Control Learning. | Gregory Lawrence, Noah J. Cowan, Stuart Russell |
| 2003 | UAI | A generalized mean field algorithm for variational inference in exponential families. | Eric P. Xing, Michael I. Jordan, Stuart Russell |
| 2002 | UAI | Decayed MCMC Filtering. | Bhaskara Marthi, Hanna Pasula, Stuart Russell, Yuval Peres |
| 2001 | AISTATS | Online Bagging and Boosting. | Nikunj C. Oza, Stuart Russell |
| 2001 | IJCAI | Approximate inference for first-order probabilistic languages. | Hanna Pasula, Stuart Russell |
| 2001 | KDD | Experimental comparisons of online and batch versions of bagging and boosting. | Nikunj C. Oza, Stuart Russell |
| 2001 | UAI | Variational MCMC. | Nando de Freitas, Pedro A. d. F. R. Hjen-Srensen, Stuart Russell |
| 2000 | ICML | Algorithms for Inverse Reinforcement Learning. | Andrew Y. Ng, Stuart Russell |
| 2000 | UAI | Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. | Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, Stuart Russell |
| 1999 | DIS | Expressive Probability Models in Science. | Stuart Russell |
| 1999 | ICML | Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping. | Andrew Y. Ng, Daishi Harada, Stuart Russell |
| 1999 | IJCAI | Convergence of Reinforcement Learning with General Function Approximators. | Vassilis A. Papavassiliou, Stuart Russell |
| 1999 | IJCAI | Tracking Many Objects with Many Sensors. | Hanna Pasula, Stuart Russell, Michael Ostland, Yaacov Ritov |
| 1998 | AAAI | Bayesian Q-Learning. | Richard Dearden, Nir Friedman, Stuart Russell |
| 1998 | AAAI | Speech Recognition with Dynamic Bayesian Networks. | Geoffrey Zweig, Stuart Russell |
| 1998 | COLT | Learning Agents for Uncertain Environments (Extended Abstract). | Stuart Russell |
| 1998 | Interspeech | Probabilistic modeling with Bayesian networks for automatic speech recognition. | Geoffrey Zweig, Stuart Russell |
| 1998 | UAI | Learning the Structure of Dynamic Probabilistic Networks. | Nir Friedman, Kevin P. Murphy, Stuart Russell |
| 1997 | IJCAI | Space-Efficient Inference in Dynamic Probabilistic Networks. | John Binder, Kevin P. Murphy, Stuart Russell |
| 1997 | IJCAI | Challenge: What is the Impact of Bayesian Networks on Learning? | Nir Friedman, Moiss Goldszmidt, David Heckerman, Stuart Russell |
| 1997 | IJCAI | Object Identification in a Bayesian Context. | Timothy Huang, Stuart Russell |
| 1997 | UAI | Image Segmentation in Video Sequences: A Probabilistic Approach. | Nir Friedman, Stuart Russell |
| 1996 | KI | Tools for Autonomous Agents (Abstract). | Stuart Russell |
| 1995 | IJCAI | The BATmobile: Towards a Bayesian Automated Taxi. | Jeff Forbes, Timothy Huang, Keiji Kanazawa, Stuart Russell |
| 1995 | IJCAI | Approximating Optimal Policies for Partially Observable Stochastic Domains. | Ronald Parr, Stuart Russell |
| 1995 | IJCAI | Rationality and Intelligence. | Stuart Russell |
| 1995 | IJCAI | Local Learning in Probabilistic Networks with Hidden Variables. | Stuart Russell, John Binder, Daphne Koller, Keiji Kanazawa |
| 1995 | UAI | Stochastic simulation algorithms for dynamic probabilistic networks. | Keiji Kanazawa, Daphne Koller, Stuart Russell |
| 1994 | AAAI | Automatic Symbolic Traffic Scene Analysis Using Belief Networks. | Timothy Huang, Daphne Koller, Jitendra Malik, Gary H. Ogasawara, Bobby S. Rao, Stuart Russell, Joseph Weber |
| 1994 | AAAI | Control Strategies for a Stochastic Planner. | Jonathan Tash, Stuart Russell |
| 1994 | ICPR | Towards robust automatic traffic scene analysis in real-time. | Daphne Koller, Joseph Weber, Timothy Huang, Jitendra Malik, Gary H. Ogasawara, Stuart Russell, Bobby S. Rao |
| 1993 | ICML | Decision Theoretic Subsampling for Induction on Large Databases. | Ron Musick, Jason Catlett, Stuart Russell |
| 1993 | IJCAI | Planning Using Multiple Execution Architectures. | Gary H. Ogasawara, Stuart Russell |
| 1993 | IJCAI | Anytime Sensing Planning and Action: A Practical Model for Robot Control. | Shlomo Zilberstein, Stuart Russell |
| 1992 | AAAI | How Long Will It Take? | Ron Musick, Stuart Russell |
| 1992 | COLT | PAC-Learnability of Determinate Logic Programs. | Saso Dzeroski, Stephen H. Muggleton, Stuart Russell |
| 1992 | ECAI | Efficient Memory-Bounded Search Methods. | Stuart Russell |
| 1989 | IJCAI | On Optimal Game-Tree Search using Rational Meta-Reasoning. | Stuart Russell, Eric Wefald |
| 1989 | UAI | Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information. | Sampath Srinivas, Stuart Russell, Alice M. Agogino |
| 1986 | AAAI | Preliminary Steps Toward the Automation of Induction. | Stuart Russell |