Stuart Russell

Orcid: 0000-0001-5252-4306

Affiliations:
  • University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, CA, USA


According to our database1, Stuart Russell authored at least 234 papers between 1986 and 2024.

Collaborative distances:

Awards

ACM Fellow

ACM Fellow 2003, "For contributions to AI and machine learning.".

Timeline

Legend:

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Bibliography

2024
Correction: AI content detection in the emerging information ecosystem: new obligations for media and tech companies.
Ethics Inf. Technol., December, 2024

AI content detection in the emerging information ecosystem: new obligations for media and tech companies.
Ethics Inf. Technol., December, 2024

Trajectory Improvement and Reward Learning from Comparative Language Feedback.
CoRR, 2024

RL, but don't do anything I wouldn't do.
CoRR, 2024

BAMDP Shaping: a Unified Theoretical Framework for Intrinsic Motivation and Reward Shaping.
CoRR, 2024

Monitoring Latent World States in Language Models with Propositional Probes.
CoRR, 2024

Evidence of Learned Look-Ahead in a Chess-Playing Neural Network.
CoRR, 2024

Diffusion On Syntax Trees For Program Synthesis.
CoRR, 2024

Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems.
CoRR, 2024

Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics.
CoRR, 2024

Social Choice for AI Alignment: Dealing with Diverse Human Feedback.
CoRR, 2024

When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning.
CoRR, 2024

Avoiding Catastrophe in Continuous Spaces by Asking for Help.
CoRR, 2024

Ethically Compliant Autonomous Systems under Partial Observability.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

A Generalized Acquisition Function for Preference-based Reward Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

AI Alignment with Changing and Influenceable Reward Functions.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Image Hijacks: Adversarial Images can Control Generative Models at Runtime.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

On Representation Complexity of Model-based and Model-free Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Effective Horizon Explains Deep RL Performance in Stochastic Environments.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Generative AI models should include detection mechanisms as a condition for public release.
Ethics Inf. Technol., December, 2023

ALMANACS: A Simulatability Benchmark for Language Model Explainability.
CoRR, 2023

Managing AI Risks in an Era of Rapid Progress.
CoRR, 2023

Active teacher selection for reinforcement learning from human feedback.
CoRR, 2023

TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI.
CoRR, 2023

Bridging RL Theory and Practice with the Effective Horizon.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Formal Composition of Robotic Systems as Contract Programs.
IROS, 2023

Adversarial Policies Beat Superhuman Go AIs.
Proceedings of the International Conference on Machine Learning, 2023

Invariance in Policy Optimisation and Partial Identifiability in Reward Learning.
Proceedings of the International Conference on Machine Learning, 2023

Who Needs to Know? Minimal Knowledge for Optimal Coordination.
Proceedings of the International Conference on Machine Learning, 2023

Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Active Reward Learning from Multiple Teachers.
Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023) co-located with the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2023

2022
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism.
IEEE Trans. Inf. Theory, 2022

Social impact and governance of AI and neurotechnologies.
Neural Networks, 2022

imitation: Clean Imitation Learning Implementations.
CoRR, 2022

Adversarial Policies Beat Professional-Level Go AIs.
CoRR, 2022

Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory.
CoRR, 2022

An Empirical Investigation of Representation Learning for Imitation.
CoRR, 2022

Provably Beneficial Artificial Intelligence.
Proceedings of the IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22, 2022

Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria.
Proceedings of the International Conference on Machine Learning, 2022

Estimating and Penalizing Induced Preference Shifts in Recommender Systems.
Proceedings of the International Conference on Machine Learning, 2022

Cross-Domain Imitation Learning via Optimal Transport.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Artificial Intelligence and the Problem of Control.
Perspectives on Digital Humanism, 2022

Human-Compatible Artificial Intelligence.
Proceedings of the Human-Like Machine Intelligence., 2022

Biography of Judea Pearl.
Proceedings of the Probabilistic and Causal Inference: The Works of Judea Pearl, 2022

2021
AI for Humanity: The Global Challenges.
Proceedings of the Reflections on Artificial Intelligence for Humanity, 2021

Trustworthy AI.
Proceedings of the Reflections on Artificial Intelligence for Humanity, 2021

Detecting Modularity in Deep Neural Networks.
CoRR, 2021

Explore and Control with Adversarial Surprise.
CoRR, 2021

The MineRL BASALT Competition on Learning from Human Feedback.
CoRR, 2021

Learning the Preferences of Uncertain Humans with Inverse Decision Theory.
CoRR, 2021

Clusterability in Neural Networks.
CoRR, 2021

Estimating and Penalizing Preference Shift in Recommender Systems.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

MADE: Exploration via Maximizing Deviation from Explored Regions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Uncertain Decisions Facilitate Better Preference Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Scalable Online Planning via Reinforcement Learning Fine-Tuning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Empirical Investigation of Representation Learning for Imitation.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Quantifying Differences in Reward Functions.
Proceedings of the 9th International Conference on Learning Representations, 2021

Accumulating Risk Capital Through Investing in Cooperation.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

PAC Learning of Causal Trees with Latent Variables.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Multi-Principal Assistance Games: Definition and Collegial Mechanisms.
CoRR, 2020

Understanding Learned Reward Functions.
CoRR, 2020

DERAIL: Diagnostic Environments for Reward And Imitation Learning.
CoRR, 2020

Multi-Principal Assistance Games.
CoRR, 2020

Neural Networks are Surprisingly Modular.
CoRR, 2020

The MAGICAL Benchmark for Robust Imitation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SLIP: Learning to predict in unknown dynamical systems with long-term memory.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Policies: Attacking Deep Reinforcement Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Artificial Intelligence: A Modern Approach (4th Edition).
Pearson, ISBN: 9781292401133, 2020

2019
Predicting human decisions with behavioral theories and machine learning.
CoRR, 2019

Cognitive model priors for predicting human decisions.
Proceedings of the 36th International Conference on Machine Learning, 2019

Bayesian Relational Memory for Semantic Visual Navigation.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Inverse reinforcement learning for video games.
CoRR, 2018

Learning and Planning with a Semantic Model.
CoRR, 2018

Meta-Learning MCMC Proposals.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Plannable Representations with Causal InfoGAN.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms.
Proceedings of the 35th International Conference on Machine Learning, 2018

An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Servant of Many Masters: Shifting priorities in Pareto-optimal sequential decision-making.
CoRR, 2017

Neural Block Sampling.
CoRR, 2017

Concurrent Hierarchical Reinforcement Learning for RoboCup Keepaway.
Proceedings of the RoboCup 2017: Robot World Cup XXI [Nagoya, Japan, July 27-31, 2017]., 2017

Inverse Reward Design.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Should Robots be Obedient?
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Adversarial Training for Relation Extraction.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

Signal-based Bayesian Seismic Monitoring.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

The Off-Switch Game.
Proceedings of the Workshops of the The Thirty-First AAAI Conference on Artificial Intelligence, 2017

A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Towards Practical Bayesian Parameter and State Estimation.
CoRR, 2016

Cooperative Inverse Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Sequential quadratic programming for task plan optimization.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Swift: Compiled Inference for Probabilistic Programming Languages.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Markovian State and Action Abstractions for MDPs via Hierarchical MCTS.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

The Physics of Text: Ontological Realism in Information Extraction.
Proceedings of the 5th Workshop on Automated Knowledge Base Construction, 2016

Metaphysics of Planning Domain Descriptions.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Probabilistic Model-Based Approach for Heart Beat Detection.
CoRR, 2015

Unifying logic and probability.
Commun. ACM, 2015

Who speaks for AI?
AI Matters, 2015

Research Priorities for Robust and Beneficial Artificial Intelligence.
AI Mag., 2015

Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter.
AI Mag., 2015

A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Multitasking: Optimal Planning for Bandit Superprocesses.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Gaussian Process Random Fields.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Tractability of Planning with Loops.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
First-Order Open-Universe POMDPs.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Fast Gaussian Process Posteriors with Product Trees.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Algorithm selection by rational metareasoning as a model of human strategy selection.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Unifying Logic and Probability: A New Dawn for AI?
Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2014

Combined task and motion planning through an extensible planner-independent interface layer.
Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

2013
Fine-Grained Decision-Theoretic Search Control
CoRR, 2013

Variational MCMC
CoRR, 2013

Product Trees for Gaussian Process Covariance in Sublinear Time.
Proceedings of the 2013 UAI Application Workshops: Big Data meet Complex Models and Models for Spatial, 2013

Rationality and Intelligence: A Brief Update.
Proceedings of the Fundamental Issues of Artificial Intelligence, 2013

Multilinear Dynamical Systems for Tensor Time Series.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

The Extended Parameter Filter.
Proceedings of the 30th International Conference on Machine Learning, 2013

Writing and sketching in the air, recognizing and controlling on the fly.
Proceedings of the 2013 ACM SIGCHI Conference on Human Factors in Computing Systems, 2013

Dynamic Scaled Sampling for Deterministic Constraints.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Graph partition strategies for generalized mean field inference
CoRR, 2012

Selecting Computations: Theory and Applications.
Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Uncertain Observation Times.
Proceedings of the Scalable Uncertainty Management - 6th International Conference, 2012

First-Order Models for POMDPs.
Proceedings of the 2nd International Workshop on Statistical Relational AI (StaRAI-12), 2012

2011
A temporally abstracted Viterbi algorithm.
Proceedings of the UAI 2011, 2011

Bounded Intention Planning.
Proceedings of the IJCAI 2011, 2011

Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System.
Proceedings of the 4th International Conference on Educational Data Mining, 2011

Global Seismic Monitoring: A Bayesian Approach.
Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, 2011

2010
Why are DBNs sparse?
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Reports of the AAAI 2010 Conference Workshops.
AI Mag., 2010

RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains.
Proceedings of the UAI 2010, 2010

Gibbs Sampling in Open-Universe Stochastic Languages.
Proceedings of the UAI 2010, 2010

Global seismic monitoring as probabilistic inference.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Modelling Glycaemia in ICU Patients - A Dynamic Bayesian Network Approach.
Proceedings of the BIOSIGNALS 2010, 2010

Combined Task and Motion Planning for Mobile Manipulation.
Proceedings of the 20th International Conference on Automated Planning and Scheduling, 2010

Hierarchical Planning for Mobile Manipulation.
Proceedings of the Bridging the Gap Between Task and Motion Planning, 2010

Automatic Inference in BLOG.
Proceedings of the Statistical Relational Artificial Intelligence, 2010

Artificial Intelligence - A Modern Approach, Third International Edition.
Pearson Education, ISBN: 978-0-13-207148-2, 2010

2009
Markov Chain Monte Carlo Data Association for Multi-Target Tracking.
IEEE Trans. Autom. Control., 2009

Technical perspective - The ultimate pilot program.
Commun. ACM, 2009

2008
Improving Gradient Estimation by Incorporating Sensor Data.
Proceedings of the UAI 2008, 2008

Probabilistic detection of short events, with application to critical care monitoring.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Angelic Hierarchical Planning: Optimal and Online Algorithms.
Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, 2008

2007
Angelic Semantics for High-Level Actions.
Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling, 2007

2006
General-Purpose MCMC Inference over Relational Structures.
Proceedings of the UAI '06, 2006

A Compact, Hierarchical Q-function Decomposition.
Proceedings of the UAI '06, 2006

First-Order Probabilistic Languages: Into the Unknown.
Proceedings of the Inductive Logic Programming, 16th International Conference, 2006

On Some Tractable Cases of Logical Filtering.
Proceedings of the Sixteenth International Conference on Automated Planning and Scheduling, 2006

2005
Efficient belief-state AND-OR search, with application to Kriegspiel.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

BLOG: Probabilistic Models with Unknown Objects.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Concurrent Hierarchical Reinforcement Learning.
Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Approximate Inference for Infinite Contingent Bayesian Networks.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004
Markov chain Monte Carlo data association for general multiple-target tracking problems.
Proceedings of the 43rd IEEE Conference on Decision and Control, 2004

Künstliche Intelligenz - ein moderner Ansatz, 2. Auflage.
Pearson Studium, ISBN: 978-3-8273-7089-1, 2004

2003
A generalized mean field algorithm for variational inference in exponential families.
Proceedings of the UAI '03, 2003

Efficient Gradient Estimation for Motor Control Learning.
Proceedings of the UAI '03, 2003

Logical Filtering.
Proceedings of the IJCAI-03, 2003

Q-Decomposition for Reinforcement Learning Agents.
Proceedings of the Machine Learning, 2003

Artificial intelligence - a modern approach, 2nd Edition.
Prentice Hall series in artificial intelligence, Prentice Hall, ISBN: 0130803022, 2003

2002
Decayed MCMC Filtering.
Proceedings of the UAI '02, 2002

Distance Metric Learning with Application to Clustering with Side-Information.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Identity Uncertainty and Citation Matching.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

State Abstraction for Programmable Reinforcement Learning Agents.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
Variational MCMC.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Experimental comparisons of online and batch versions of bagging and boosting.
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining, 2001

Approximate inference for first-order probabilistic languages.
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, 2001

Online Bagging and Boosting.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.
Proceedings of the Sequential Monte Carlo Methods in Practice, 2001

2000
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks.
Proceedings of the UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30, 2000

Programmable Reinforcement Learning Agents.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Algorithms for Inverse Reinforcement Learning.
Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford University, Stanford, CA, USA, June 29, 2000

1999
Tracking Many Objects with Many Sensors.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

Convergence of Reinforcement Learning with General Function Approximators.
Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, 1999

Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping.
Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27, 1999

Expressive Probability Models in Science.
Proceedings of the Discovery Science, 1999

1998
Learning from Examples and Membership Queries with Structured Determinations.
Mach. Learn., 1998

Object Identification: A Bayesian Analysis with Application to Traffic Surveillance.
Artif. Intell., 1998

Learning the Structure of Dynamic Probabilistic Networks.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

Probabilistic modeling with Bayesian networks for automatic speech recognition.
Proceedings of the 5th International Conference on Spoken Language Processing, Incorporating The 7th Australian International Speech Science and Technology Conference, Sydney Convention Centre, Sydney, Australia, 30th November, 1998

Learning Agents for Uncertain Environments (Extended Abstract).
Proceedings of the Eleventh Annual Conference on Computational Learning Theory, 1998

Speech Recognition with Dynamic Bayesian Networks.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

Bayesian Q-Learning.
Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1997
Adaptive Probabilistic Networks with Hidden Variables.
Mach. Learn., 1997

PNPACK: Computing with Probabilities in Java.
Concurr. Pract. Exp., 1997

Rationality and Intelligence.
Artif. Intell., 1997

Image Segmentation in Video Sequences: A Probabilistic Approach.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Learning in Rational Agents.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Reinforcement Learning with Hierarchies of Machines.
Proceedings of the Advances in Neural Information Processing Systems 10, 1997

Object Identification in a Bayesian Context.
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

Challenge: What is the Impact of Bayesian Networks on Learning?
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

Space-Efficient Inference in Dynamic Probabilistic Networks.
Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

Uncertain Learning Agents (Abstract).
Proceedings of the Machine Learning: ECML-97, 1997

1996
Optimal Composition of Real-Time Systems.
Artif. Intell., 1996

Tools for Autonomous Agents (Abstract).
Proceedings of the KI-96: Advances in Artificial Intelligence, 1996

Machine Learning.
Proceedings of the Artificial Intelligence, 1996

1995
A Modern, Agent-Oriented Approach to Introductory Artificial Intelligence.
SIGART Bull., 1995

Provably Bounded-Optimal Agents.
J. Artif. Intell. Res., 1995

Stochastic simulation algorithms for dynamic probabilistic networks.
Proceedings of the UAI '95: Proceedings of the Eleventh Annual Conference on Uncertainty in Artificial Intelligence, 1995

Local Learning in Probabilistic Networks with Hidden Variables.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

Approximating Optimal Policies for Partially Observable Stochastic Domains.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

The BATmobile: Towards a Bayesian Automated Taxi.
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, 1995

Artificial intelligence - a modern approach: the intelligent agent book.
Prentice Hall series in artificial intelligence, Prentice Hall, ISBN: 0-13-360124-2, 1995

1994
Towards robust automatic traffic scene analysis in real-time.
Proceedings of the 12th IAPR International Conference on Pattern Recognition, 1994

Control Strategies for a Stochastic Planner.
Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994

Automatic Symbolic Traffic Scene Analysis Using Belief Networks.
Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994

1993
Anytime Sensing Planning and Action: A Practical Model for Robot Control.
Proceedings of the 13th International Joint Conference on Artificial Intelligence. Chambéry, France, August 28, 1993

Provably Bounded Optimal Agents.
Proceedings of the 13th International Joint Conference on Artificial Intelligence. Chambéry, France, August 28, 1993

Planning Using Multiple Execution Architectures.
Proceedings of the 13th International Joint Conference on Artificial Intelligence. Chambéry, France, August 28, 1993

Decision Theoretic Subsampling for Induction on Large Databases.
Proceedings of the Machine Learning, 1993

Learnability of Constrained Logic Programs.
Proceedings of the Machine Learning: ECML-93, 1993

1992
Efficient Memory-Bounded Search Methods.
Proceedings of the 10th European Conference on Artificial Intelligence, 1992

PAC-Learnability of Determinate Logic Programs.
Proceedings of the Fifth Annual ACM Conference on Computational Learning Theory, 1992

How Long Will It Take?
Proceedings of the 10th National Conference on Artificial Intelligence, 1992

1991
An Architecture for Bounded Rationality.
SIGART Bull., 1991

Prior knowledge and autonomous learning.
Robotics Auton. Syst., 1991

Principles of Metareasoning.
Artif. Intell., 1991

Composing Real-Time Systems.
Proceedings of the 12th International Joint Conference on Artificial Intelligence. Sydney, 1991

Do the right thing - studies in limited rationality.
MIT Press, ISBN: 978-0-262-18144-0, 1991

1989
Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information.
Proceedings of the UAI '89: Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence, 1989

On Optimal Game-Tree Search using Rational Meta-Reasoning.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Execution Architectures and Compilation.
Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Adaptive Learning of Decision-Theoretic Search Control Knowledge.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

Declarative Bias for Structural Domains.
Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1988
Boundaries of Operationality.
Proceedings of the Machine Learning, 1988

Tree-Structured Bias.
Proceedings of the 7th National Conference on Artificial Intelligence, 1988

IMEX: Overcoming Intactability In Explanation Based Learning.
Proceedings of the 7th National Conference on Artificial Intelligence, 1988

1987
A Logical Approach to Reasoning by Analogy.
Proceedings of the 10th International Joint Conference on Artificial Intelligence. Milan, 1987

A Declarative Approach to Bias in Concept Learning.
Proceedings of the 6th National Conference on Artificial Intelligence. Seattle, 1987

1986
Preliminary Steps Toward the Automation of Induction.
Proceedings of the 5th National Conference on Artificial Intelligence. Philadelphia, 1986

Quantitative Analysis of Analogy.
Proceedings of the 5th National Conference on Artificial Intelligence. Philadelphia, 1986


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