Quantitative Analysis of Analogy. - Stuart J. Russell (AAAI, 1986)

Preliminary Steps Toward the Automation of Induction. - Stuart Russell 001 (AAAI, 1986)

A Declarative Approach to Bias in Concept Learning. - Stuart J. Russell; Benjamin N. Grosof (AAAI, 1987)

A Logical Approach to Reasoning by Analogy. - Todd R. Davies; Stuart J. Russell (IJCAI, 1987)

IMEX: Overcoming Intactability In Explanation Based Learning. - Michael S. Braverman; Stuart J. Russell (AAAI, 1988)

Tree-Structured Bias. - Stuart J. Russell (AAAI, 1988)

Boundaries of Operationality. - Michael S. Braverman; Stuart J. Russell (ML, 1988)

Declarative Bias for Structural Domains. - Benjamin N. Grosof; Stuart J. Russell (ML, 1989)

Adaptive Learning of Decision-Theoretic Search Control Knowledge. - Eric Wefald; Stuart J. Russell (ML, 1989)

Execution Architectures and Compilation. - Stuart J. Russell (IJCAI, 1989)

On Optimal Game-Tree Search using Rational Meta-Reasoning. - Stuart Russell 001; Eric Wefald (IJCAI, 1989)

Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information. - Sampath Srinivas; Stuart Russell 001; Alice M. Agogino (UAI, 1989)

Do the right thing - studies in limited rationality. - Stuart J. Russell; Eric Wefald (MIT Press, 1991)

Composing Real-Time Systems. - Stuart J. Russell; Shlomo Zilberstein (IJCAI, 1991)

Principles of Metareasoning. - Stuart Russell 001; Eric Wefald (Artif. Intell., 1991)

Prior knowledge and autonomous learning. - Stuart J. Russell (Robotics Auton. Syst., 1991)

An Architecture for Bounded Rationality. - Stuart J. Russell (SIGART Bull., 1991)

How Long Will It Take? - Ron Musick; Stuart Russell 001 (AAAI, 1992)

PAC-Learnability of Determinate Logic Programs. - Saso Dzeroski; Stephen H. Muggleton; Stuart Russell 001 (COLT, 1992)

Efficient Memory-Bounded Search Methods. - Stuart Russell 001 (ECAI, 1992)

Learnability of Constrained Logic Programs. - Saso Dzeroski; Stephen H. Muggleton; Stuart Russell 001 (ECML, 1993)

Decision Theoretic Subsampling for Induction on Large Databases. - Ron Musick; Jason Catlett; Stuart Russell 001 (ICML, 1993)

Planning Using Multiple Execution Architectures. - Gary H. Ogasawara; Stuart Russell 001 (IJCAI, 1993)

Provably Bounded Optimal Agents. - Stuart J. Russell; Devika Subramanian; Ronald Parr (IJCAI, 1993)

Anytime Sensing Planning and Action: A Practical Model for Robot Control. - Shlomo Zilberstein; Stuart Russell 001 (IJCAI, 1993)

Automatic Symbolic Traffic Scene Analysis Using Belief Networks. - Timothy Huang; Daphne Koller; Jitendra Malik; Gary H. Ogasawara; Bobby S. Rao; Stuart Russell 001; Joseph Weber (AAAI, 1994)

Control Strategies for a Stochastic Planner. - Jonathan Tash; Stuart Russell 001 (AAAI, 1994)

Towards robust automatic traffic scene analysis in real-time. - Daphne Koller; Joseph Weber; Timothy Huang; Jitendra Malik; Gary H. Ogasawara; Stuart Russell 001; Bobby S. Rao (ICPR (1), 1994)

Artificial intelligence - a modern approach: the intelligent agent book. - Stuart J. Russell; Peter Norvig (Prentice Hall, 1995)

The BATmobile: Towards a Bayesian Automated Taxi. - Jeff Forbes 001; Timothy Huang; Keiji Kanazawa; Stuart Russell 001 (IJCAI, 1995)

Approximating Optimal Policies for Partially Observable Stochastic Domains. - Ronald Parr; Stuart Russell 001 (IJCAI, 1995)

Local Learning in Probabilistic Networks with Hidden Variables. - Stuart Russell 001; John Binder; Daphne Koller; Keiji Kanazawa (IJCAI, 1995)

Stochastic simulation algorithms for dynamic probabilistic networks. - Keiji Kanazawa; Daphne Koller; Stuart Russell 001 (UAI, 1995)

Provably Bounded-Optimal Agents. - Stuart J. Russell; Devika Subramanian (J. Artif. Intell. Res., 1995)

A Modern, Agent-Oriented Approach to Introductory Artificial Intelligence. - Stuart Russell 001; Peter Norvig (SIGART Bull., 1995)

Machine Learning. - Stuart Russell 001 (Artificial Intelligence, 1996)

Tools for Autonomous Agents (Abstract). - Stuart Russell 001 (KI, 1996)

Optimal Composition of Real-Time Systems. - Shlomo Zilberstein; Stuart Russell 001 (Artif. Intell., 1996)

Uncertain Learning Agents (Abstract). - Stuart Russell 001 (ECML, 1997)

Space-Efficient Inference in Dynamic Probabilistic Networks. - John Binder; Kevin P. Murphy; Stuart Russell 001 (IJCAI, 1997)

Challenge: What is the Impact of Bayesian Networks on Learning? - Nir Friedman; Moisés Goldszmidt; David Heckerman; Stuart Russell 001 (IJCAI (1), 1997)

Object Identification in a Bayesian Context. - Timothy Huang; Stuart Russell 001 (IJCAI, 1997)

Reinforcement Learning with Hierarchies of Machines. - Ronald Parr; Stuart Russell 001 (NIPS, 1997)

Learning in Rational Agents. - Stuart Russell 001 (NIPS, 1997)

Image Segmentation in Video Sequences: A Probabilistic Approach. - Nir Friedman; Stuart Russell 001 (UAI, 1997)

Rationality and Intelligence. - Stuart J. Russell (Artif. Intell., 1997)

PNPACK: Computing with Probabilities in Java. - Stuart Russell 001; Lewis Stiller; Othar Hansson (Concurr. Pract. Exp., 1997)

Adaptive Probabilistic Networks with Hidden Variables. - John Binder; Daphne Koller; Stuart Russell 001; Keiji Kanazawa (Mach. Learn., 1997)

Bayesian Q-Learning. - Richard Dearden; Nir Friedman; Stuart Russell 001 (AAAI/IAAI, 1998)

Speech Recognition with Dynamic Bayesian Networks. - Geoffrey Zweig; Stuart Russell 001 (AAAI/IAAI, 1998)

Learning Agents for Uncertain Environments (Extended Abstract). - Stuart Russell 001 (COLT, 1998)

Probabilistic modeling with Bayesian networks for automatic speech recognition. - Geoffrey Zweig; Stuart Russell 001 (ICSLP, 1998)

Learning the Structure of Dynamic Probabilistic Networks. - Nir Friedman; Kevin P. Murphy; Stuart Russell 001 (UAI, 1998)

Object Identification: A Bayesian Analysis with Application to Traffic Surveillance. - Timothy Huang; Stuart Russell 001 (Artif. Intell., 1998)

Learning from Examples and Membership Queries with Structured Determinations. - Prasad Tadepalli; Stuart Russell 001 (Mach. Learn., 1998)

Expressive Probability Models in Science. - Stuart Russell 001 (Discovery Science, 1999)

Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping. - Andrew Y. Ng; Daishi Harada; Stuart Russell 001 (ICML, 1999)

Convergence of Reinforcement Learning with General Function Approximators. - Vassilis A. Papavassiliou; Stuart Russell 001 (IJCAI, 1999)

Tracking Many Objects with Many Sensors. - Hanna Pasula; Stuart Russell 001; Michael Ostland; Yaacov Ritov (IJCAI, 1999)

Algorithms for Inverse Reinforcement Learning. - Andrew Y. Ng; Stuart Russell 001 (ICML, 2000)

Programmable Reinforcement Learning Agents. - David Andre; Stuart J. Russell (NIPS, 2000)

Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. - Arnaud Doucet; Nando de Freitas; Kevin P. Murphy; Stuart Russell 001 (UAI, 2000)

Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. - Kevin Murphy 002; Stuart Russell 001 (Sequential Monte Carlo Methods in Practice, 2001)

Online Bagging and Boosting. - Nikunj C. Oza; Stuart Russell 001 (AISTATS, 2001)

Approximate inference for first-order probabilistic languages. - Hanna Pasula; Stuart Russell 001 (IJCAI, 2001)

Experimental comparisons of online and batch versions of bagging and boosting. - Nikunj C. Oza; Stuart Russell 001 (KDD, 2001)

Variational MCMC. - Nando de Freitas; Pedro A. d. F. R. Højen-Sørensen; Stuart Russell 001 (UAI, 2001)

State Abstraction for Programmable Reinforcement Learning Agents. - David Andre; Stuart J. Russell (AAAI/IAAI, 2002)

Identity Uncertainty and Citation Matching. - Hanna Pasula; Bhaskara Marthi; Brian Milch; Stuart Russell 001; Ilya Shpitser (NIPS, 2002)

A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences. - Eric P. Xing; Michael I. Jordan; Richard M. Karp; Stuart Russell 001 (NIPS, 2002)

Distance Metric Learning with Application to Clustering with Side-Information. - Eric P. Xing; Andrew Y. Ng; Michael I. Jordan; Stuart Russell 001 (NIPS, 2002)

Decayed MCMC Filtering. - Bhaskara Marthi; Hanna Pasula; Stuart Russell 001; Yuval Peres (UAI, 2002)

Artificial intelligence - a modern approach, 2nd Edition. - Stuart Russell 001; Peter Norvig (Prentice Hall, 2003)

Q-Decomposition for Reinforcement Learning Agents. - Stuart Russell 001; Andrew Zimdars (ICML, 2003)

Logical Filtering. - Eyal Amir; Stuart Russell 001 (IJCAI, 2003)

Efficient Gradient Estimation for Motor Control Learning. - Gregory Lawrence; Noah J. Cowan; Stuart Russell 001 (UAI, 2003)

A generalized mean field algorithm for variational inference in exponential families. - Eric P. Xing; Michael I. Jordan; Stuart Russell 001 (UAI, 2003)

Künstliche Intelligenz - ein moderner Ansatz, 2. Auflage. - Stuart Russell 001; Peter Norvig (Pearson Studium, 2004)

Markov chain Monte Carlo data association for general multiple-target tracking problems. - Songhwai Oh; Stuart Russell 001; Shankar Sastry 001 (CDC, 2004)

Approximate Inference for Infinite Contingent Bayesian Networks. - Brian Milch; Bhaskara Marthi; David A. Sontag; Stuart Russell 001; Daniel L. Ong; Andrey Kolobov (AISTATS, 2005)

Concurrent Hierarchical Reinforcement Learning. - Bhaskara Marthi; Stuart Russell 001; David Latham; Carlos Guestrin (IJCAI, 2005)

BLOG: Probabilistic Models with Unknown Objects. - Brian Milch; Bhaskara Marthi; Stuart Russell 001; David A. Sontag; Daniel L. Ong; Andrey Kolobov (IJCAI, 2005)

Efficient belief-state AND-OR search, with application to Kriegspiel. - Stuart Russell 001; Jason Andrew Wolfe (IJCAI, 2005)

On Some Tractable Cases of Logical Filtering. - T. K. Satish Kumar; Stuart Russell 001 (ICAPS, 2006)

First-Order Probabilistic Languages: Into the Unknown. - Brian Milch; Stuart Russell 001 (ILP, 2006)

A Compact, Hierarchical Q-function Decomposition. - Bhaskara Marthi; Stuart Russell 001; David Andre (UAI, 2006)

General-Purpose MCMC Inference over Relational Structures. - Brian Milch; Stuart Russell 001 (UAI, 2006)

Angelic Semantics for High-Level Actions. - Bhaskara Marthi; Stuart Russell 001; Jason Andrew Wolfe (ICAPS, 2007)

Angelic Hierarchical Planning: Optimal and Online Algorithms. - Bhaskara Marthi; Stuart Russell 001; Jason Andrew Wolfe (ICAPS, 2008)

Probabilistic detection of short events, with application to critical care monitoring. - Norm Aleks; Stuart Russell 001; Michael G. Madden; Diane Morabito; Kristan Staudenmayer; Mitchell J. Cohen; Geoffrey T. Manley (NIPS, 2008)

Improving Gradient Estimation by Incorporating Sensor Data. - Gregory Lawrence; Stuart Russell 001 (UAI, 2008)

Anytime Lifted Belief Propagation. - Rodrigo de Salvo Braz; Sriraam Natarajan; Hung Bui 001; Jude W. Shavlik; Stuart Russell 001 (MLG/SRL@ILP, 2009)

Technical perspective - The ultimate pilot program. - Stuart Russell 001; Lawrence K. Saul (Commun. ACM, 2009)

Markov Chain Monte Carlo Data Association for Multi-Target Tracking. - Songhwai Oh; Stuart Russell 001; Shankar Sastry 001 (IEEE Trans. Autom. Control., 2009)

Artificial Intelligence - A Modern Approach, Third International Edition. - Stuart J. Russell; Peter Norvig (Pearson Education, 2010)

Automatic Inference in BLOG. - Nimar S. Arora; Stuart Russell 001; Erik B. Sudderth (StarAI@AAAI, 2010)

Hierarchical Planning for Mobile Manipulation. - Jason Andrew Wolfe; Bhaskara Marthi; Stuart Russell 001 (Bridging the Gap Between Task and Motion Planning, 2010)

Combined Task and Motion Planning for Mobile Manipulation. - Jason Andrew Wolfe; Bhaskara Marthi; Stuart Russell 001 (ICAPS, 2010)

Modelling Glycaemia in ICU Patients - A Dynamic Bayesian Network Approach. - Catherine G. Enright; Michael G. Madden; Stuart Russell 001; Norm Aleks; Geoffrey T. Manley; John G. Laffey; Brian Harte; Anne Mulvey; Niall Madden (BIOSIGNALS, 2010)

Global seismic monitoring as probabilistic inference. - Nimar S. Arora; Stuart Russell 001; Paul Kidwell; Erik B. Sudderth (NIPS, 2010)

Gibbs Sampling in Open-Universe Stochastic Languages. - Nimar S. Arora; Rodrigo de Salvo Braz; Erik B. Sudderth; Stuart Russell 001 (UAI, 2010)

RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains. - Emma Brunskill; Stuart Russell 001 (UAI, 2010)

Reports of the AAAI 2010 Conference Workshops. - David W. Aha; Mark S. Boddy; Vadim Bulitko; Artur S. d'Avila Garcez; Prashant Doshi; Stefan Edelkamp; Christopher W. Geib; Piotr J. Gmytrasiewicz; Robert P. Goldman; Pascal Hitzler; Charles L. Isbell Jr.; Darsana P. Josyula; et al. (AI Mag., 2010)

Why are DBNs sparse? - Shaunak Chatterjee; Stuart Russell 001 (AISTATS, 2010)

Global Seismic Monitoring: A Bayesian Approach. - Nimar S. Arora; Stuart Russell 001; Paul Kidwell; Erik B. Sudderth (AAAI, 2011)

Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System. - Emma Brunskill; Stuart Russell 001 (EDM, 2011)

Bounded Intention Planning. - Jason Andrew Wolfe; Stuart Russell 001 (IJCAI, 2011)

A temporally abstracted Viterbi algorithm. - Shaunak Chatterjee; Stuart Russell 001 (UAI, 2011)

First-Order Models for POMDPs. - Siddharth Srivastava 001; Stuart Russell 001; Avi Pfeffer (StarAI@UAI, 2012)

Uncertain Observation Times. - Shaunak Chatterjee; Stuart Russell 001 (SUM, 2012)

Selecting Computations: Theory and Applications. - Nicholas Hay; Stuart Russell 001; David Tolpin; Solomon Eyal Shimony (UAI, 2012)

Graph partition strategies for generalized mean field inference - Eric P. Xing; Michael I. Jordan; Stuart Russell 001 (CoRR, 2012)

Dynamic Scaled Sampling for Deterministic Constraints. - Lei Li 005; Bharath Ramsundar; Stuart Russell 001 (AISTATS, 2013)

Writing and sketching in the air, recognizing and controlling on the fly. - Sharad Vikram; Lei Li 005; Stuart Russell 001 (CHI Extended Abstracts, 2013)

The Extended Parameter Filter. - Yusuf Erol; Lei Li 005; Bharath Ramsundar; Stuart Russell 001 (ICML (3), 2013)

Multilinear Dynamical Systems for Tensor Time Series. - Mark Rogers; Lei Li 005; Stuart Russell 001 (NIPS, 2013)

Rationality and Intelligence: A Brief Update. - Stuart Russell 001 (PT-AI, 2013)

Product Trees for Gaussian Process Covariance in Sublinear Time. - David A. Moore; Stuart Russell 001 (UAI Application Workshops, 2013)

Variational MCMC - Nando de Freitas; Pedro A. d. F. R. Højen-Sørensen; Michael I. Jordan; Stuart Russell 001 (CoRR, 2013)

Fine-Grained Decision-Theoretic Search Control - Stuart Russell 001 (CoRR, 2013)

Combined task and motion planning through an extensible planner-independent interface layer. - Siddharth Srivastava 001; Eugene Fang; Lorenzo Riano; Rohan Chitnis; Stuart Russell 001; Pieter Abbeel (ICRA, 2014)

Unifying Logic and Probability: A New Dawn for AI? - Stuart Russell 001 (IPMU (1), 2014)

Algorithm selection by rational metareasoning as a model of human strategy selection. - Falk Lieder; Dillon Plunkett; Jessica B. Hamrick; Stuart J. Russell; Nicholas Hay; Thomas L. Griffiths 001 (NIPS, 2014)

Fast Gaussian Process Posteriors with Product Trees. - David A. Moore; Stuart Russell 001 (UAI, 2014)

First-Order Open-Universe POMDPs. - Siddharth Srivastava 001; Stuart Russell 001; Paul Ruan; Xiang Cheng 006 (UAI, 2014)

Tractability of Planning with Loops. - Siddharth Srivastava 001; Shlomo Zilberstein; Abhishek Gupta 004; Pieter Abbeel; Stuart Russell 001 (AAAI, 2015)

Gaussian Process Random Fields. - David A. Moore; Stuart J. Russell (NIPS, 2015)

Multitasking: Optimal Planning for Bandit Superprocesses. - Dylan Hadfield-Menell; Stuart Russell 001 (UAI, 2015)

A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC. - Wei Wang; Stuart Russell 001 (UAI, 2015)

Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter. - Stuart Russell 001; Tom Dietterich; Eric Horvitz; Bart Selman; Francesca Rossi 001; Demis Hassabis; Shane Legg; Mustafa Suleyman; Dileep George; D. Scott Phoenix (AI Mag., 2015)

Research Priorities for Robust and Beneficial Artificial Intelligence. - Stuart Russell 001; Daniel Dewey; Max Tegmark (AI Mag., 2015)

Who speaks for AI? - Eric Eaton; Tom Dietterich; Maria L. Gini; Barbara J. Grosz; Charles L. Isbell Jr.; Subbarao Kambhampati; Michael L. Littman; Francesca Rossi 001; Stuart Russell 001; Peter Stone 001; Toby Walsh; Michael J. Wooldridge (AI Matters, 2015)

Unifying logic and probability. - Stuart Russell 001 (Commun. ACM, 2015)

Probabilistic Model-Based Approach for Heart Beat Detection. - Hugh Chen; Yusuf Erol; Eric Shen; Stuart Russell 001 (CoRR, 2015)

Metaphysics of Planning Domain Descriptions. - Siddharth Srivastava 001; Stuart Russell 001; Alessandro Pinto (AAAI, 2016)

The Physics of Text: Ontological Realism in Information Extraction. - Stuart Russell 001; Ole Torp Lassen; Justin Uang; Wei Wang (AKBC@NAACL-HLT, 2016)

Markovian State and Action Abstractions for MDPs via Hierarchical MCTS. - Aijun Bai; Siddharth Srivastava 001; Stuart Russell 001 (IJCAI, 2016)

Swift: Compiled Inference for Probabilistic Programming Languages. - Yi Wu 013; Lei Li 005; Stuart Russell 001; Rastislav Bodík (IJCAI, 2016)

Sequential quadratic programming for task plan optimization. - Dylan Hadfield-Menell; Christopher Lin; Rohan Chitnis; Stuart Russell 001; Pieter Abbeel (IROS, 2016)

Cooperative Inverse Reinforcement Learning. - Dylan Hadfield-Menell; Stuart Russell 001; Pieter Abbeel; Anca D. Dragan (NIPS, 2016)

Towards Practical Bayesian Parameter and State Estimation. - Yusuf Bugra Erol; Yi Wu 013; Lei Li 005; Stuart Russell 001 (CoRR, 2016)

A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models. - Yusuf Bugra Erol; Yi Wu 013; Lei Li 005; Stuart Russell 001 (AAAI, 2017)

The Off-Switch Game. - Dylan Hadfield-Menell; Anca D. Dragan; Pieter Abbeel; Stuart Russell 001 (AAAI Workshops, 2017)

Signal-based Bayesian Seismic Monitoring. - David A. Moore; Stuart Russell 001 (AISTATS, 2017)

Adversarial Training for Relation Extraction. - Yi Wu 013; David Bamman; Stuart Russell 001 (EMNLP, 2017)

Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions. - Aijun Bai; Stuart Russell 001 (IJCAI, 2017)

Should Robots be Obedient? - Smitha Milli; Dylan Hadfield-Menell; Anca D. Dragan; Stuart Russell 001 (IJCAI, 2017)

Inverse Reward Design. - Dylan Hadfield-Menell; Smitha Milli; Pieter Abbeel; Stuart J. Russell; Anca D. Dragan (NIPS, 2017)

Concurrent Hierarchical Reinforcement Learning for RoboCup Keepaway. - Aijun Bai; Stuart Russell 001; Xiaoping Chen (RoboCup, 2017)

Neural Block Sampling. - Tongzhou Wang 001; Yi Wu 013; David A. Moore; Stuart J. Russell (CoRR, 2017)

Servant of Many Masters: Shifting priorities in Pareto-optimal sequential decision-making. - Andrew Critch; Stuart Russell 001 (CoRR, 2017)

An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning. - Dhruv Malik; Malayandi Palaniappan; Jaime F. Fisac; Dylan Hadfield-Menell; Stuart Russell 001; Anca D. Dragan (ICML, 2018)

Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms. - Yi Wu 013; Siddharth Srivastava 001; Nicholas Hay; Simon S. Du; Stuart Russell 001 (ICML, 2018)

Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making. - Nishant Desai; Andrew Critch; Stuart J. Russell (NeurIPS, 2018)

Learning Plannable Representations with Causal InfoGAN. - Thanard Kurutach; Aviv Tamar; Ge Yang 003; Stuart J. Russell; Pieter Abbeel (NeurIPS, 2018)

Meta-Learning MCMC Proposals. - Tongzhou Wang 001; Yi Wu 013; Dave Moore; Stuart J. Russell (NeurIPS, 2018)

Learning and Planning with a Semantic Model. - Yi Wu 013; Yuxin Wu; Aviv Tamar; Stuart Russell 001; Georgia Gkioxari; Yuandong Tian (CoRR, 2018)

Inverse reinforcement learning for video games. - Aaron Tucker; Adam Gleave; Stuart Russell 001 (CoRR, 2018)

Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient. - Shihui Li; Yi Wu 013; Xinyue Cui; Honghua Dong; Fei Fang 001; Stuart Russell 001 (AAAI, 2019)

Bayesian Relational Memory for Semantic Visual Navigation. - Yi Wu 013; Yuxin Wu; Aviv Tamar; Stuart Russell 001; Georgia Gkioxari; Yuandong Tian (ICCV, 2019)

Cognitive model priors for predicting human decisions. - David D. Bourgin; Joshua C. Peterson; Daniel Reichman 001; Stuart J. Russell; Thomas L. Griffiths 001 (ICML, 2019)

Predicting human decisions with behavioral theories and machine learning. - Ori Plonsky; Reut Apel; Eyal Ert; Moshe Tennenholtz; David Bourgin; Joshua C. Peterson; Daniel Reichman 001; Thomas L. Griffiths 001; Stuart J. Russell; Evan C. Carter; James F. Cavanagh; Ido Erev (CoRR, 2019)

Artificial Intelligence: A Modern Approach (4th Edition). - Stuart Russell 001; Peter Norvig (Pearson, 2020)

Adversarial Policies: Attacking Deep Reinforcement Learning. - Adam Gleave; Michael Dennis 001; Cody Wild; Neel Kant; Sergey Levine; Stuart Russell 001 (ICLR, 2020)

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design. - Michael Dennis 001; Natasha Jaques; Eugene Vinitsky; Alexandre M. Bayen; Stuart Russell 001; Andrew Critch; Sergey Levine (NeurIPS, 2020)

SLIP: Learning to predict in unknown dynamical systems with long-term memory. - Paria Rashidinejad; Jiantao Jiao; Stuart Russell 001 (NeurIPS, 2020)

The MAGICAL Benchmark for Robust Imitation. - Sam Toyer; Rohin Shah; Andrew Critch; Stuart Russell 001 (NeurIPS, 2020)

Neural Networks are Surprisingly Modular. - Daniel Filan; Shlomi Hod; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2020)

Multi-Principal Assistance Games. - Arnaud Fickinger; Simon Zhuang; Dylan Hadfield-Menell; Stuart Russell 001 (CoRR, 2020)

DERAIL: Diagnostic Environments for Reward And Imitation Learning. - Pedro Freire; Adam Gleave; Sam Toyer; Stuart Russell 001 (CoRR, 2020)

Understanding Learned Reward Functions. - Eric J. Michaud; Adam Gleave; Stuart Russell 001 (CoRR, 2020)

Multi-Principal Assistance Games: Definition and Collegial Mechanisms. - Arnaud Fickinger; Simon Zhuang; Andrew Critch; Dylan Hadfield-Menell; Stuart Russell 001 (CoRR, 2020)

PAC Learning of Causal Trees with Latent Variables. - Prasad Tadepalli; Stuart J. Russell (AAAI, 2021)

Accumulating Risk Capital Through Investing in Cooperation. - Charlotte Roman; Michael Dennis 001; Andrew Critch; Stuart Russell 001 (AAMAS, 2021)

Quantifying Differences in Reward Functions. - Adam Gleave; Michael Dennis 001; Shane Legg; Stuart Russell 001; Jan Leike (ICLR, 2021)

An Empirical Investigation of Representation Learning for Imitation. - Cynthia Chen; Xin Chen; Sam Toyer; Cody Wild; Scott Emmons; Ian Fischer; Kuang-Huei Lee; Neel Alex; Steven H. Wang; Ping Luo; Stuart Russell 001; Pieter Abbeel; et al. (NeurIPS Datasets and Benchmarks, 2021)

Scalable Online Planning via Reinforcement Learning Fine-Tuning. - Arnaud Fickinger; Hengyuan Hu; Brandon Amos; Stuart J. Russell; Noam Brown (NeurIPS, 2021)

Uncertain Decisions Facilitate Better Preference Learning. - Cassidy Laidlaw; Stuart Russell 001 (NeurIPS, 2021)

MADE: Exploration via Maximizing Deviation from Explored Regions. - Tianjun Zhang; Paria Rashidinejad; Jiantao Jiao; Yuandong Tian; Joseph E. Gonzalez; Stuart Russell 001 (NeurIPS, 2021)

Estimating and Penalizing Preference Shift in Recommender Systems. - Micah Carroll; Dylan Hadfield-Menell; Stuart Russell 001; Anca D. Dragan (RecSys, 2021)

Clusterability in Neural Networks. - Daniel Filan; Stephen Casper; Shlomi Hod; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2021)

Learning the Preferences of Uncertain Humans with Inverse Decision Theory. - Cassidy Laidlaw; Stuart Russell 001 (CoRR, 2021)

The MineRL BASALT Competition on Learning from Human Feedback. - Rohin Shah; Cody Wild; Steven H. Wang; Neel Alex; Brandon Houghton; William H. Guss; Sharada P. Mohanty; Anssi Kanervisto; Stephanie Milani; Nicholay Topin; Pieter Abbeel; Stuart Russell 001; et al. (CoRR, 2021)

Explore and Control with Adversarial Surprise. - Arnaud Fickinger; Natasha Jaques; Samyak Parajuli; Michael Chang 003; Nicholas Rhinehart; Glen Berseth; Stuart Russell 001; Sergey Levine (CoRR, 2021)

Detecting Modularity in Deep Neural Networks. - Shlomi Hod; Stephen Casper; Daniel Filan; Cody Wild; Andrew Critch; Stuart Russell 001 (CoRR, 2021)

Trustworthy AI. - Raja Chatila 001; Virginia Dignum; Michael Fisher 001; Fosca Giannotti; Katharina Morik; Stuart Russell 001; Karen Yeung (Reflections on Artificial Intelligence for Humanity, 2021)

AI for Humanity: The Global Challenges. - Jocelyn Maclure; Stuart Russell 001 (Reflections on Artificial Intelligence for Humanity, 2021)

Biography of Judea Pearl. - Stuart J. Russell (Probabilistic and Causal Inference, 2022)

Human-Compatible Artificial Intelligence. - Stuart Russell 001 (Human-Like Machine Intelligence, 2022)

Artificial Intelligence and the Problem of Control. - Stuart Russell 001 (Perspectives on Digital Humanism, 2022)

Cross-Domain Imitation Learning via Optimal Transport. - Arnaud Fickinger; Samuel Cohen; Stuart Russell 001; Brandon Amos (ICLR, 2022)

Estimating and Penalizing Induced Preference Shifts in Recommender Systems. - Micah D. Carroll; Anca D. Dragan; Stuart Russell 001; Dylan Hadfield-Menell (ICML, 2022)

For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria. - Scott Emmons; Caspar Oesterheld; Andrew Critch; Vincent Conitzer; Stuart Russell 001 (ICML, 2022)

Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning. - Samer B. Nashed; Justin Svegliato; Abhinav Bhatia; Stuart Russell 001; Shlomo Zilberstein (IROS, 2022)

Provably Beneficial Artificial Intelligence. - Stuart Russell 001 (IUI, 2022)

An Empirical Investigation of Representation Learning for Imitation. - Xin Chen; Sam Toyer; Cody Wild; Scott Emmons; Ian Fischer; Kuang-Huei Lee; Neel Alex; Steven H. Wang; Ping Luo; Stuart Russell 001; Pieter Abbeel; Rohin Shah (CoRR, 2022)

Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory. - Andrew Critch; Michael Dennis 001; Stuart Russell 001 (CoRR, 2022)

Adversarial Policies Beat Professional-Level Go AIs. - Tony Tong Wang; Adam Gleave; Nora Belrose; Tom Tseng; Joseph Miller; Michael D. Dennis; Yawen Duan; Viktor Pogrebniak; Sergey Levine; Stuart Russell 001 (CoRR, 2022)

imitation: Clean Imitation Learning Implementations. - Adam Gleave; Mohammad Taufeeque; Juan Rocamonde; Erik Jenner; Steven H. Wang; Sam Toyer; Maximilian Ernestus; Nora Belrose; Scott Emmons; Stuart Russell 001 (CoRR, 2022)

Social impact and governance of AI and neurotechnologies. - Kenji Doya; Arisa Ema; Hiroaki Kitano; Masamichi Sakagami; Stuart Russell 001 (Neural Networks, 2022)

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. - Paria Rashidinejad; Banghua Zhu; Cong Ma 001; Jiantao Jiao; Stuart Russell 001 (IEEE Trans. Inf. Theory, 2022)

Active Reward Learning from Multiple Teachers. - Peter Barnett; Rachel Freedman; Justin Svegliato; Stuart Russell 001 (SafeAI@AAAI, 2023)

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals. - Alexander K. Lew; George Matheos; Tan Zhi-Xuan; Matin Ghavamizadeh; Nishad Gothoskar; Stuart Russell 001; Vikash K. Mansinghka (AISTATS, 2023)

Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian. - Paria Rashidinejad; Hanlin Zhu; Kunhe Yang; Stuart Russell 001; Jiantao Jiao (ICLR, 2023)

Who Needs to Know? Minimal Knowledge for Optimal Coordination. - Niklas Lauffer; Ameesh Shah; Micah Carroll; Michael D. Dennis; Stuart Russell 001 (ICML, 2023)

Invariance in Policy Optimisation and Partial Identifiability in Reward Learning. - Joar Max Viktor Skalse; Matthew Farrugia-Roberts; Stuart Russell 001; Alessandro Abate; Adam Gleave (ICML, 2023)

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 001 (ICML, 2023)

Formal Composition of Robotic Systems as Contract Programs. - Mason Nakamura; Justin Svegliato; Samer B. Nashed; Shlomo Zilberstein; Stuart Russell 001 (IROS, 2023)

Bridging RL Theory and Practice with the Effective Horizon. - Cassidy Laidlaw; Stuart J. Russell; Anca D. Dragan (NeurIPS, 2023)

TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI. - Andrew Critch; Stuart Russell 001 (CoRR, 2023)

Active teacher selection for reinforcement learning from human feedback. - Rachel Freedman; Justin Svegliato; Kyle Hollins Wray; Stuart Russell 001 (CoRR, 2023)

Managing AI Risks in an Era of Rapid Progress. - 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; et al. (CoRR, 2023)

ALMANACS: A Simulatability Benchmark for Language Model Explainability. - Edmund Mills; Shiye Su; Stuart Russell 001; Scott Emmons (CoRR, 2023)

Generative AI models should include detection mechanisms as a condition for public release. - Alistair Knott; Dino Pedreschi; Raja Chatila 001; Tapabrata Chakraborti; Susan Leavy; Ricardo Baeza-Yates; David M. Eyers; Andrew Trotman; Paul D. Teal; Przemyslaw Biecek; Stuart Russell 001; Yoshua Bengio (Ethics Inf. Technol., 2023)

Trajectory Improvement and Reward Learning from Comparative Language Feedback. - Zhaojing Yang; Miru Jun; Jeremy Tien; Stuart Russell 001; Anca D. Dragan; Erdem Biyik (CoRL, 2024)

The Effective Horizon Explains Deep RL Performance in Stochastic Environments. - Cassidy Laidlaw; Banghua Zhu; Stuart Russell 001; Anca D. Dragan (ICLR, 2024)

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 001 (ICLR, 2024)

On Representation Complexity of Model-based and Model-free Reinforcement Learning. - Hanlin Zhu; Baihe Huang; Stuart Russell 001 (ICLR, 2024)

Image Hijacks: Adversarial Images can Control Generative Models at Runtime. - Luke Bailey; Euan Ong; Stuart Russell 001; Scott Emmons (ICML, 2024)

AI Alignment with Changing and Influenceable Reward Functions. - Micah Carroll; Davis Foote; Anand Siththaranjan; Stuart Russell 001; Anca D. Dragan (ICML, 2024)

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 001; Milan Mossé; Eric Pacuit; Stuart Russell 001; Hailey Schoelkopf; Emanuel Tewolde; William S. Zwicker (ICML, 2024)

A Generalized Acquisition Function for Preference-based Reward Learning. - Evan Ellis; Gaurav R. Ghosal; Stuart J. Russell; Anca D. Dragan; Erdem Biyik (ICRA, 2024)

Ethically Compliant Autonomous Systems under Partial Observability. - Qingyuan Lu; Justin Svegliato; Samer B. Nashed; Shlomo Zilberstein; Stuart Russell 001 (ICRA, 2024)

Evidence of Learned Look-Ahead in a Chess-Playing Neural Network. - Erik Jenner; Shreyas Kapur; Vasil Georgiev; Cameron Allen; Scott Emmons; Stuart J. Russell (NeurIPS, 2024)

When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback. - Leon Lang; Davis Foote; Stuart J. Russell; Anca D. Dragan; Erik Jenner; Scott Emmons (NeurIPS, 2024)

Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. - Hanlin Zhu; Baihe Huang; Shaolun Zhang; Michael I. Jordan; Jiantao Jiao; Yuandong Tian; Stuart J. Russell (NeurIPS, 2024)

Avoiding Catastrophe in Continuous Spaces by Asking for Help. - Benjamin Plaut; Hanlin Zhu; Stuart Russell 001 (CoRR, 2024)

When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning. - Leon Lang; Davis Foote; Stuart Russell 001; Anca D. Dragan; Erik Jenner; Scott Emmons (CoRR, 2024)

Social Choice for AI Alignment: Dealing with Diverse Human Feedback. - Vincent Conitzer; Rachel Freedman; Jobst Heitzig; Wesley H. Holliday; Bob M. Jacobs; Nathan Lambert 001; Milan Mossé; Eric Pacuit; Stuart Russell 001; Hailey Schoelkopf; Emanuel Tewolde; William S. Zwicker (CoRR, 2024)

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems. - David Dalrymple; Joar Skalse; Yoshua Bengio; Stuart Russell 001; Max Tegmark; Sanjit Seshia; Steve Omohundro; Christian Szegedy; Ben Goldhaber; Nora Ammann; Alessandro Abate; Joe Halpern; et al. (CoRR, 2024)

BAMDP Shaping: a Unified Theoretical Framework for Intrinsic Motivation and Reward Shaping. - Aly Lidayan; Michael Dennis 001; Stuart Russell 001 (CoRR, 2024)

Will an AI with Private Information Allow Itself to Be Switched Off? - Andrew Garber; Rohan Subramani; Linus Luu; Mark Bedaywi; Stuart Russell 001; Scott Emmons (CoRR, 2024)

Extractive Structures Learned in Pretraining Enable Generalization on Finetuned Facts. - Jiahai Feng; Stuart Russell 001; Jacob Steinhardt (CoRR, 2024)

International Scientific Report on the Safety of Advanced AI (Interim Report). - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi 001; Danielle Goldfarb; Hoda Heidari; Leila Khalatbari; Shayne Longpre; Vasilios Mavroudis; et al. (CoRR, 2024)

Observation Interference in Partially Observable Assistance Games. - Scott Emmons; Caspar Oesterheld; Vincent Conitzer; Stuart Russell 001 (CoRR, 2024)

AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies. - Alistair Knott; Dino Pedreschi; Toshiya Jitsuzumi; Susan Leavy; David M. Eyers; Tapabrata Chakraborti; Andrew Trotman; Sundar Sundareswaran; Ricardo Baeza-Yates; Przemyslaw Biecek; Adrian Weller; Paul D. Teal; et al. (Ethics Inf. Technol., 2024)

The Partially Observable Off-Switch Game. - Andrew Garber; Rohan Subramani; Linus Luu; Mark Bedaywi; Stuart Russell 001; Scott Emmons (AAAI, 2025)

Monitoring Latent World States in Language Models with Propositional Probes. - Jiahai Feng; Stuart Russell 001; Jacob Steinhardt (ICLR, 2025)

Diffusion On Syntax Trees For Program Synthesis. - Shreyas Kapur; Erik Jenner; Stuart Russell 001 (ICLR, 2025)

BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping. - Aly Lidayan; Michael D. Dennis; Stuart Russell 001 (ICLR, 2025)

RL, but don't do anything I wouldn't do. - Michael K. Cohen; Marcus Hutter; Yoshua Bengio; Stuart Russell 001 (UAI, 2025)

International AI Safety Report. - Yoshua Bengio; Sören Mindermann; Daniel Privitera; Tamay Besiroglu; Rishi Bommasani; Stephen Casper; Yejin Choi 001; Philip Fox; Ben Garfinkel; Danielle Goldfarb; Hoda Heidari; Anson Ho; et al. (CoRR, 2025)

How Do LLMs Perform Two-Hop Reasoning in Context? - Tianyu Guo 004; Hanlin Zhu; Ruiqi Zhang; Jiantao Jiao; Song Mei; Michael I. Jordan; Stuart Russell 001 (CoRR, 2025)

Asking for Help Enables Safety Guarantees Without Sacrificing Effectiveness. - Benjamin Plaut; Juan Liévano-Karim; Stuart Russell 001 (CoRR, 2025)

AssistanceZero: Scalably Solving Assistance Games. - Cassidy Laidlaw; Eli Bronstein; Timothy Guo; Dylan Feng; Lukas Berglund; Justin Svegliato; Stuart Russell 001; Anca D. Dragan (CoRR, 2025)

Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought. - Hanlin Zhu; Shibo Hao; Zhiting Hu; Jiantao Jiao; Stuart Russell 001; Yuandong Tian (CoRR, 2025)

Provable Sim-to-Real Transfer via Offline Domain Randomization. - Arnaud Fickinger; Abderrahim Bendahi; Stuart Russell 001 (CoRR, 2025)

Generalization or Hallucination? Understanding Out-of-Context Reasoning in Transformers. - Yixiao Huang 004; Hanlin Zhu; Tianyu Guo 004; Jiantao Jiao; Somayeh Sojoudi; Michael I. Jordan; Stuart Russell 001; Song Mei (CoRR, 2025)

The Singapore Consensus on Global AI Safety Research Priorities. - Yoshua Bengio; Tegan Maharaj; Luke Ong; Stuart Russell 001; Dawn Song; Max Tegmark; Lan Xue; Ya-Qin Zhang; Stephen Casper; Wan Sie Lee; Sören Mindermann; Vanessa Wilfred; et al. (CoRR, 2025)