Stuart J. Russell
#353
Most Influential Person Now
English-American computer scientist, (1962 - ), Portsmouth, England, United Kingdom
Stuart J. Russell's AcademicInfluence.com Rankings
Stuart J. Russellcomputer-science Degrees
Computer Science
#29
World Rank
#29
Historical Rank
Artificial Intelligence
#3
World Rank
#3
Historical Rank
Machine Learning
#7
World Rank
#7
Historical Rank
Database
#154
World Rank
#159
Historical Rank
Download Badge
Computer Science
Stuart J. Russell's Degrees
- PhD Computer Science Stanford University
- Bachelors Physics University of Oxford
Similar Degrees You Can Earn
Why Is Stuart J. Russell Influential?
(Suggest an Edit or Addition)According to Wikipedia, Stuart Jonathan Russell is a British computer scientist known for his contributions to artificial intelligence . He is a professor of computer science at the University of California, Berkeley and was from 2008 to 2011 an adjunct professor of neurological surgery at the University of California, San Francisco. He holds the Smith-Zadeh Chair in Engineering at University of California, Berkeley. He founded and leads the Center for Human-Compatible Artificial Intelligence at UC Berkeley. Russell is the co-author with Peter Norvig of the authoritative textbook of the field of AI: Artificial Intelligence: A Modern Approach used in more than 1,500 universities in 135 countries.
Stuart J. Russell's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Artificial Intelligence: A Modern Approach (1995) (27994)
- Distance Metric Learning with Application to Clustering with Side-Information (2002) (3206)
- Dynamic bayesian networks: representation, inference and learning (2002) (2856)
- Pharmacokinetics of a novel formulation of ivermectin after administration to goats (2000) (2744)
- Artificial intelligence - a modern approach, 2nd Edition (2003) (2033)
- Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping (1999) (1833)
- Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks (2000) (1438)
- Image Segmentation in Video Sequences: A Probabilistic Approach (1997) (1049)
- Online bagging and boosting (2005) (925)
- Reinforcement Learning with Hierarchies of Machines (1997) (823)
- Learning the Structure of Dynamic Probabilistic Networks (1998) (696)
- BLOG: Probabilistic Models with Unknown Objects (2005) (546)
- Research Priorities for Robust and Beneficial Artificial Intelligence (2015) (518)
- Cooperative Inverse Reinforcement Learning (2016) (455)
- Bayesian Q-Learning (1998) (449)
- Combined task and motion planning through an extensible planner-independent interface layer (2014) (429)
- Do the right thing (1991) (428)
- Rationality and Intelligence (1995) (427)
- Do the right thing - studies in limited rationality (1991) (418)
- Principles of Metareasoning (1989) (404)
- Adaptive Probabilistic Networks with Hidden Variables (1997) (397)
- Towards robust automatic traffic scene analysis in real-time (1994) (372)
- Identity Uncertainty and Citation Matching (2002) (359)
- Stochastic simulation algorithms for dynamic probabilistic networks (1995) (304)
- Provably Bounded Optimal Agents (1993) (302)
- Markov chain Monte Carlo data association for general multiple-target tracking problems (2004) (295)
- State abstraction for programmable reinforcement learning agents (2002) (281)
- Speech Recognition with Dynamic Bayesian Networks (1998) (275)
- Experimental comparisons of online and batch versions of bagging and boosting (2001) (268)
- Inverse Reward Design (2017) (261)
- Learning agents for uncertain environments (extended abstract) (1998) (244)
- A generalized mean field algorithm for variational inference in exponential families (2002) (239)
- The BATmobile: Towards a Bayesian Automated Taxi (1995) (226)
- Object Identification in a Bayesian Context (1997) (224)
- Optimal Composition of Real-Time Systems (1996) (219)
- Adversarial Policies: Attacking Deep Reinforcement Learning (2019) (215)
- Approximating Optimal Policies for Partially Observable Stochastic Domains (1995) (213)
- Tracking Many Objects with Many Sensors (1999) (210)
- Combined Task and Motion Planning for Mobile Manipulation (2010) (206)
- A Logical Approach to Reasoning by Analogy (1987) (197)
- Local Learning in Probabilistic Networks with Hidden Variables (1995) (191)
- Efficient Memory-Bounded Search Methods (1992) (186)
- Adversarial Training for Relation Extraction (2017) (185)
- Composing Real-Time Systems (1991) (182)
- Automatic Symbolic Traffic Scene Analysis Using Belief Networks (1994) (177)
- Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient (2019) (172)
- Q-Decomposition for Reinforcement Learning Agents (2003) (156)
- PAC-learnability of determinate logic programs (1992) (151)
- Anytime Sensing Planning and Action: A Practical Model for Robot Control (1993) (144)
- Learning Plannable Representations with Causal InfoGAN (2018) (142)
- Approximate Reasoning Using Anytime Algorithms (1995) (140)
- Programmable Reinforcement Learning Agents (2000) (136)
- A modern, agent-oriented approach to introductory artificial intelligence (1995) (126)
- NP-Completeness of Searches for Smallest Possible Feature Sets (1994) (121)
- Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism (2021) (119)
- Inteligencia Artificial: un Enfoque Moderno (2013) (117)
- Variational MCMC (2001) (106)
- Artificial Intelligence (1999) (103)
- Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design (2020) (101)
- Object Identification: A Bayesian Analysis with Application to Traffic Surveillance (1998) (100)
- Probabilistic models with unknown objects (2006) (89)
- On Optimal Game-Tree Search using Rational Meta-Reasoning (1989) (87)
- The Off-Switch Game (2016) (87)
- Robotics: Ethics of artificial intelligence (2015) (79)
- Unifying logic and probability (2015) (79)
- Angelic Semantics for High-Level Actions (2007) (78)
- Bayesian Relational Memory for Semantic Visual Navigation (2019) (74)
- Selecting Computations: Theory and Applications (2012) (73)
- General-Purpose MCMC Inference over Relational Structures (2006) (72)
- Approximate Inference for Infinite Contingent Bayesian Networks (2005) (72)
- Automated Construction of Sparse Bayesian Networks from Unstructured Probabilistic Models and Domain Information (2013) (70)
- Artificial intelligence - a modern approach: the intelligent agent book (1995) (70)
- Stephen Hawking: \'Transcendence looks at the implications of artificial intelligence - but are we taking AI seriously enough?\' (2014) (70)
- A Declarative Approach to Bias in Concept Learning (1987) (67)
- Decision Theoretic Subsampling for Induction on Large Databases (1993) (67)
- Rationality and Intelligence: A Brief Update (2013) (66)
- Multitasking (2018) (66)
- Multilinear Dynamical Systems for Tensor Time Series (2013) (64)
- Angelic Hierarchical Planning: Optimal and Online Algorithms (2008) (64)
- BLOG: Relational Modeling with Unknown Objects (2004) (64)
- Approximate inference for first-order probabilistic languages (2001) (64)
- Artificial intelligence. Fears of an AI pioneer. (2015) (63)
- Control Strategies for a Stochastic Planner (1994) (60)
- The compleat guide to MRS (1985) (59)
- Artificial Intelligence - A Modern Approach, Third International Edition (2010) (58)
- First-Order Probabilistic Languages: Into the Unknown (2007) (57)
- Space-Efficient Inference in Dynamic Probabilistic Networks (1997) (56)
- A quantitative analysis of analogy by similarity (1986) (53)
- Analogical and inductive reasoning (1987) (52)
- Cognitive Model Priors for Predicting Human Decisions (2019) (51)
- Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter (2015) (49)
- Probabilistic modeling with Bayesian networks for automatic speech recognition (1998) (48)
- Markovian State and Action Abstractions for MDPs via Hierarchical MCTS (2016) (47)
- Algorithm selection by rational metareasoning as a model of human strategy selection (2014) (45)
- Tree-Structured Bias (1988) (45)
- Logical Filtering (2003) (44)
- Analogy by Similarity (1988) (42)
- Should We Fear Supersmart Robots? (2016) (42)
- A Hierarchical Bayesian Markovian Model for Motifs in Biopolymer Sequences (2002) (41)
- Should Robots be Obedient? (2017) (40)
- Using Classical Planners for Tasks with Continuous Operators in Robotics (2013) (40)
- Preliminary Steps Toward the Automation of Induction (1986) (39)
- Challenge: What is the Impact of Bayesian Networks on Learning? (1997) (39)
- Efficient Gradient Estimation for Motor Control Learning (2002) (37)
- Efficient belief-state AND-OR search, with application to Kriegspiel (2005) (36)
- How Long Will It Take? (1992) (35)
- EBOOK : Artificial Intelligence, A Modern Approach, 3rd edition (2010) (35)
- Execution Architectures and Compilation (1989) (34)
- Efficient resource-bounded reasoning in AT-RALPH (1992) (34)
- Predicting human decisions with behavioral theories and machine learning (2019) (32)
- Handbook of Perception and Cognition (2011) (31)
- Decayed MCMC Filtering (2012) (31)
- Reinforcement learning for autonomous vehicles (2002) (31)
- Rationality as an explanation of language (1987) (30)
- Probabilistic detection of short events, with application to critical care monitoring (2008) (29)
- Writing and sketching in the air, recognizing and controlling on the fly (2013) (29)
- Meta-Learning MCMC Proposals (2017) (28)
- Quantifying Differences in Reward Functions (2020) (28)
- Inverse reinforcement learning for video games (2018) (28)
- First-Order Probabilistic Models for Information Extraction (2003) (27)
- Declarative Bias: An Overview (1990) (27)
- Artificial intelligence: The future is superintelligent (2017) (26)
- Swift: Compiled Inference for Probabilistic Programming Languages (2016) (26)
- Adaptive Probabilistic Networks (1994) (26)
- Artificial Intelligence (1986) (26)
- RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains (2010) (25)
- First-Order Open-Universe POMDPs (2014) (25)
- Convergence of Reinforcement Learning with General Function Approximators (1999) (25)
- Eecient Memory-bounded Search Methods (1992) (25)
- Metaphysics of Planning Domain Descriptions (2016) (24)
- Boundaries of Operationality (1988) (24)
- Discrete-Continuous Mixtures in Probabilistic Programming: Generalized Semantics and Inference Algorithms (2018) (23)
- Decayed MCMC iltering (2002) (23)
- Stratagus-playing Agents in Concurrent ALisp (22)
- Decision-Theoretic Control of Reasoning: General Theory and an (1988) (21)
- Machine Learning, Proceedings of the Twelfth International Conference on Machine Learning, Tahoe City, California, USA, July 9-12, 1995 (1995) (20)
- The MAGICAL Benchmark for Robust Imitation (2020) (20)
- A Sketch of Autonomous Learning using Declarative Bias (1990) (20)
- Shift of Bias as Non-Monotonic Reasoning (1990) (19)
- Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions (2017) (19)
- An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning (2018) (19)
- Partially Observable Sequential Decision Making for Problem Selection in an Intelligent Tutoring System (2011) (18)
- Analogy and Single-Instance Generalization (1987) (18)
- Metareasoning for Monte Carlo Tree Search (2011) (17)
- The MineRL BASALT Competition on Learning from Human Feedback (2021) (17)
- Learning from Examples and Membership Queries with Structured Determinations (1998) (17)
- Clusterability in Neural Networks (2021) (17)
- Gaussian Process Random Fields (2015) (17)
- Tractability of Planning with Loops (2015) (17)
- A temporally abstracted Viterbi algorithm (2011) (16)
- MADE: Exploration via Maximizing Deviation from Explored Regions (2021) (16)
- Exploiting locality in probabilistic inference (2004) (16)
- Learning and Planning with a Semantic Model (2018) (15)
- Sequential quadratic programming for task plan optimization (2016) (15)
- Learnability of Constrained Logic Programs (1993) (15)
- Adaptive Learning of Decision-Theoretic Search Control Knowledge (1989) (15)
- Fine-Grained Decision-Theoretic Search Control (2013) (14)
- Cross-Domain Imitation Learning via Optimal Transport (2021) (13)
- Probabilistic model-based approach for heart beat detection (2015) (13)
- Why are DBNs sparse? (2010) (13)
- Benefits of Assistance over Reward Learning (2020) (13)
- An Empirical Investigation of Representation Learning for Imitation (2022) (12)
- Estimating and Penalizing Induced Preference Shifts in Recommender Systems (2022) (12)
- Declarative Bias for Structural Domains (1989) (11)
- The Extended Parameter Filter (2013) (11)
- Extending Bayesian Networks to the Open-Universe Case (2009) (11)
- Bounded Intention Planning (2011) (11)
- An architecture for bounded rationality (1991) (11)
- Planning Using Multiple Execution Architectures (1993) (11)
- Prior knowledge and autonomous learning (1991) (11)
- Mutual Constraints on Representation and Inference (1990) (11)
- A Smart-Dumb/Dumb-Smart Algorithm for Efficient Split-Merge MCMC (2015) (11)
- Artificial Intelligence (2020) (10)
- Understanding Learned Reward Functions (2020) (10)
- IMEX: Overcoming Intactability In Explanation Based Learning (1988) (10)
- Extended abstract: Learning search strategies (1999) (10)
- Unifying Logic and Probability: A New Dawn for AI? (2014) (9)
- Dynamic Scaled Sampling for Deterministic Constraints (2013) (9)
- Estimating and Penalizing Preference Shift in Recommender Systems (2021) (9)
- Scalable Online Planning via Reinforcement Learning Fine-Tuning (2021) (9)
- Neural Networks are Surprisingly Modular (2020) (8)
- Compositional Modeling with DPNs (1997) (8)
- Invariance in Policy Optimisation and Partial Identifiability in Reward Learning (2022) (8)
- Angelic Hierarchical Planning: Optimal and Online Algorithms (Revised) (2009) (8)
- Detecting Modularity in Deep Neural Networks (2021) (7)
- SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory (2020) (7)
- Human-Compatible Artificial Intelligence (2021) (7)
- Signal-based Bayesian Seismic Monitoring (2017) (7)
- Probabilistic graphical models and algorithms for genomic analysis (2004) (7)
- Inductive learning by machines (1991) (7)
- Modelling Glycaemia in ICU Patients - A Dynamic Bayesian Network Approach (2010) (7)
- Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian (2022) (6)
- Uncertain Decisions Facilitate Better Preference Learning (2021) (6)
- On Some Tractable Cases of Logical Filtering (2006) (6)
- A compact, hierarchically optimal Q-function decomposition (2006) (6)
- A Compact, Hierarchical Q-function Decomposition (2012) (6)
- Trustworthy AI (2021) (5)
- Bayesian problem-solving applied to scheduling (1998) (5)
- It's not too soon to be wary of AI: We need to act now to protect humanity from future superintelligent machines (2019) (5)
- Automated Pricing Agents in the On-Demand Economy (2016) (5)
- Negotiable Reinforcement Learning for Pareto Optimal Sequential Decision-Making (2018) (5)
- Expressive Probability Models in Science (1999) (5)
- Complete Guide to MRS (1985) (5)
- Artificial Intelligence and the Problem of Control (2021) (5)
- Pruned Neural Networks are Surprisingly Modular (2020) (4)
- Object Identi cation : A Bayesian Analysiswith Application to Tra c Surveillance 1 (1998) (4)
- Exploiting Belief State Structure in Graph Search (2007) (4)
- Multi-Principal Assistance Games (2020) (4)
- Explore and Control with Adversarial Surprise (2021) (4)
- DERAIL: Diagnostic Environments for Reward And Imitation Learning (2020) (4)
- Fast Gaussian Process Posteriors with Product Trees (2014) (4)
- Quantifying Local Specialization in Deep Neural Networks (2021) (4)
- First-Order Open-Universe POMDPs: Formulation and Algorithms (2013) (4)
- PAC Learning of Causal Trees with Latent Variables (2021) (4)
- Handbook of Perception and Cognition , Vol . 14 Chapter 4 : Machine Learning (2007) (3)
- Cooperative and uncooperative institution designs: Surprises and problems in open-source game theory (2022) (3)
- Social impact and governance of AI and neurotechnologies (2022) (3)
- Multi-Principal Assistance Games: Definition and Collegial Mechanisms (2020) (3)
- Machine Learning (1996) (3)
- PNPACK: Computing with Probabilities in Java (1997) (3)
- Concurrent Hierarchical Reinforcement Learning for RoboCup Keepaway (2017) (3)
- A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models (2017) (3)
- Combined State and Parameter Estimation of Human Intracranial Hemodynamics (2013) (2)
- Model Based Probabilistic Inference for Intensive Care Medicine (2015) (2)
- Accumulating Risk Capital Through Investing in Cooperation (2021) (2)
- Neural Block Sampling (2017) (2)
- Who speaks for AI? (2016) (2)
- The Physics of Text: Ontological Realism in Information Extraction (2016) (2)
- Servant of Many Masters: Shifting priorities in Pareto-optimal sequential decision-making (2017) (2)
- Probabilistic modeling of sensor artifacts in critical care (2008) (2)
- Expressive Probability Models For Speech Recognition And Understanding (1999) (2)
- Learning in Rational Agents (1997) (2)
- Quantitative Analysis of Analogy (1986) (2)
- Efficient Cooperative Inverse Reinforcement Learning (2017) (2)
- BFiT: From Possible-World Semantics to Random-Evaluation Semantics in an Open Universe (2014) (2)
- Unifying Logic and Probability : Recent Developments (2014) (1)
- Uncertain Observation Times (2012) (1)
- For Learning in Symmetric Teams, Local Optima are Global Nash Equilibria (2022) (1)
- Reports of the AAAI 2010 Conference Workshops (2010) (1)
- 146 Modeling and Machine Learning of Cerebrovascular Dynamics. (2012) (1)
- Learning a Semantic Prior for Guided Navigation (2018) (1)
- Technical perspectiveThe ultimate pilot program (2009) (1)
- Selecting the Partial State Abstractions of MDPs: A Metareasoning Approach with Deep Reinforcement Learning (2022) (1)
- Title Feasibility Study Of Fully Autonomous Vehicles Using Decision-theoretic Control Permalink (2000) (1)
- Control of Mobile Robots Using Anytime Computation (1992) (1)
- Distributed acoustic sensing for infrastructure (2017) (0)
- Source Materials (2020) (0)
- Stuart Russell ANALOGY BY SIMILARITY (0)
- Temporal Logical Filtering - Preliminary Results (2002) (0)
- Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach (2020) (0)
- New light on RV Tau variables. (1997) (0)
- Proceedings 37th International Conference on Logic Programming (Technical Communications) (2021) (0)
- Two Techniques for Tractable Decision-Theoretic Planning* (1994) (0)
- Electric light cables and the distribution of electricity (2010) (0)
- Towards Limited Rational Agents (2003) (0)
- If We Succeed (2022) (0)
- Learning the Preferences of Uncertain Humans with Inverse Decision Theory (2021) (0)
- Value determination with function approximation (2003) (0)
- Learning the Value of Computation (2003) (0)
- Efficient motor control learning (2009) (0)
- Supplementary Material for "SLIP: Learning to Predict in Unknown Dynamical Systems with Long-Term Memory" (2021) (0)
- Application to Game-Playing (2003) (0)
- Application to Problem-Solving Search (2003) (0)
- The Future of (Artificial) Intelligence (2015) (0)
- Control Strategies for a tochastic Planner (1994) (0)
- Bridging RL Theory and Practice with the Effective Horizon (2023) (0)
- Hierarchical Planning for Mobile Manipulation (2010) (0)
- Decision-Theoretic Planning with Multiple Execution Architectures* (1993) (0)
- Compositional Modeling With DPNsGeo (1997) (0)
- Multitasking: Optimal Planning for Bandit Superprocesses (2015) (0)
- imitation: Clean Imitation Learning Implementations (2022) (0)
- Active Reward Learning from Multiple Teachers (2023) (0)
- Statistical Relational Artificial Intelligence, Papers from the 2010 AAAI Workshop, Atlanta, Georgia, USA, July 12, 2010 (2010) (0)
- Open-Universe Theory for Bayesian Inference, Decision, and Sensing (OUTBIDS) (2014) (0)
- Product Trees for Gaussian Process Covariance in Sublinear Time (2013) (0)
- Value Determination with General Function Approximators (2000) (0)
- Uncertain Learning Agents (Abstract) (1997) (0)
- Syllabus COSC 5365 Artificial Intelligence (2006) (0)
- Towards Practical Bayesian Parameter and State Estimation (2016) (0)
- Commentary on Baum ’ s " How a Bayesian . . ? (0)
- Object Identiication: a Bayesian Analysis with Application to Traac Surveillance 1 (2009) (0)
- Tools for Autonomous Agents (Abstract) (1996) (0)
- Improving Gradient Estimation by Incorporating Sensor Data (2008) (0)
- Resources on Existential Risk General Blockinscholarly Blockindiscussion Blockinof Blockinexistential Blockinrisk (0)
- 1 APPROXIMATE REASONING USING ANYTIME ALGORITHMS (1994) (0)
- Joint State and Parameter Estimation in Temporal Models by Yusuf Bugra (2018) (0)
- AI for Humanity: The Global Challenges (2021) (0)
- vercoming Hntr ctability in Err ased Learning (1988) (0)
- Applications of distributed acoustic sensing for security and surveillance (2017) (0)
This paper list is powered by the following services:
Other Resources About Stuart J. Russell
What Schools Are Affiliated With Stuart J. Russell?
Stuart J. Russell is affiliated with the following schools:
