Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

   

Faculty Publications - Stuart J. Russell

Books

  • S. Russell, P. Norvig, J. F. Canny, J. Malik, and D. D. Edwards, Artificial Intelligence: A Modern Approach, 2nd ed., Prentice Hall Series in Artificial Intelligence, Upper Saddle River, NJ: Prentice Hall/Pearson Education, 2003. [abstract]
  • S. J. Russell and P. Norvig, Solution Manual for "Artificial Intelligence: A Modern Approach", 2nd ed., Prentice Hall Series in Artificial Intelligence, Upper Saddle River, NJ: Prentice Hall, 2003.
  • S. Russell, P. Norvig, J. F. Canny, J. Malik, and D. D. Edwards, Artificial Intelligence: A Modern Approach, Prentice Hall Series in Artificial Intelligence, Englewood Cliffs, NJ: Prentice Hall, 1995. [abstract]
  • S. Russell and E. Wefald, Do the Right Thing: Studies in Limited Rationality, Cambridge, MA: MIT Press, 1991. [abstract]
  • S. Russell, The Use of Knowledge in Analogy and Induction, Research Notes in Artificial Intelligence, London: Pitman, 1989. [abstract]

Book chapters or sections

  • B. Milch, B. Marthi, S. J. Russell, D. Sontag, D. L. Ong, and A. Kolobov, "BLOG: Probabilistic Models with Unknown Objects," in Introduction to Statistical Relational Learning, L. Getoor and B. Taskar, Eds., Adaptive Computation and Machine Learning, Cambridge, MA: MIT Press, 2007, pp. 373-398.
  • B. Milch and S. J. Russell, "First-order probabilistic languages: Into the unknown," in Inductive Logic Programming: Proc. 16th Intl. Conf. (ILP 2006). Revised Selected Papers, S. Muggleton, R. Otero, and A. Tamaddoni-Nezhad, Eds., Lecture Notes in Artificial Intelligence, Vol. 4455, Berlin, Germany: Springer-Verlag, 2007, pp. 10-24.
  • H. Pasula, B. Marthi, B. Milch, S. J. Russell, and I. Shpitser, "Identity uncertainty and citation matching," in Proc. 16th Annual Advances in Neural Information Processing Systems (NIPS 2002), S. Becker, S. Thrun, and K. Obermayer, Eds., Bradford Books, Vol. 15, Cambridge, MA: MIT Press, 2003, pp. 1425-1432.
  • E. P. Xing, A. Y. Ng, M. Jordan, and S. J. Russell, "Distance metric learning with application to clustering with side-information," in Proc. 16th Annual Advances in Neural Information Processing Systems (NIPS 2002), S. Becker, S. Thrun, and K. Obermayer, Eds., Bradford Books, Vol. 15, Cambridge, MA: MIT Press, 2003, pp. 521-528.
  • E. P. Xing, M. Jordan, R. M. Karp, and S. J. Russell, "A hierarchical Bayesian Markovian model for motifs in biopolymer sequences," in Proc. 16th Annual Advances in Neural Information Processing Systems (NIPS 2002), S. Becker, S. Thrun, and K. Obermayer, Eds., Bradford Books, Vol. 15, Cambridge, MA: MIT Press, 2003, pp. 1513-1520.
  • J. Pearl and S. J. Russell, "Bayesian Networks," in The Handbook of Brain Theory and Neural Networks, M. A. Arbib, Ed., 2 ed., Bradford Books, Cambridge, MA: MIT Press, 2002, pp. 157-160.
  • S. J. Russell, "Rationality and Intelligence," in Common Sense, Reasoning, and Rationality, R. Elio, Ed., New Directions in Cognitive Science, New York, NY: Oxford University Press, 2002, pp. 37-59.
  • K. Murphy and S. J. Russell, "Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks," in Sequential Monte Carlo Methods in Practice, A. Doucet, N. de Freitas, and N. Gordon, Eds., Statistics for Engineering and Information Science, New York, NY: Springer-Verlag New York, Inc., 2001, pp. 499-516.
  • D. Andre and S. J. Russell, "Programmable reinforcement learning agents," in Advances in Neural Information Processing Systems 13: Proc. 14th Annual Conf. (NIPS 2000), T. K. Leen, T. G. Dietterich, and V. Tresp, Eds., Bradford Books, Vol. 13, Cambridge, MA: MIT Press, 2001, pp. 1019-1025.
  • S. J. Russell, "Expressive probability models in science (Invited Paper)," in Discovery Science: Proc. 2nd Intl. Conf. (DS 1999), S. Arikawa and K. Furukawa, Eds., Lecture Notes in Artificial Intelligence, Vol. 1721, Berlin, Germany: Springer-Verlag, 2000, pp. 13-16.
  • S. J. Russell, "Metareasoning," in The MIT Encyclopedia of the Cognitive Sciences (MITECS), R. A. Wilson and F. C. Keil, Eds., Bradford Books, Cambridge, MA: MIT Press, 1999, pp. 539-541.
  • M. Jordan and S. J. Russell, "Computational Intelligence (Prefatory Material)," in The MIT Encyclopedia of the Cognitive Sciences (MITECS), R. A. Wilson and F. C. Keil, Eds., Bradford Books, Cambridge, MA: MIT Press, 1999, pp. lxxiii-xc.
  • R. Parr and S. J. Russell, "Reinforcement learning with hierarchies of machines," in Advances in Neural Information Processing Systems 10: Proc. 11th Annual Conf. (NIPS 1997), M. Jordan, M. J. Kearns, and S. A. Solla, Eds., Bradford Books, Vol. 10, Cambridge, MA: MIT Press, 1998, pp. 1043-1049.
  • S. J. Russell, "Uncertain Learning Agents (Abstract) (Invited Talk)," in Machine Learning: Proc. 9th European Conf. (ECML-1997), M. van Someren and G. Widmer, Eds., Lecture Notes in Artificial Intelligence, Vol. 1224, Berlin, Germany: Springer-Verlag, 1997, pp. 3-3.
  • S. J. Russell, "Tools for Autonomous Agents (Abstract) (Invited Talk)," in Advances in Artificial Intelligence: Proc. 20th Annual German Conf. on Artificial Intelligence (KI-1996), G. Gorz and S. Holldobler, Eds., Lecture Notes in Artificial Intelligence, Vol. 1137, Berlin, Germany: Springer-Verlag, 1996, pp. 331-331.
  • S. J. Russell, "Machine Learning," in Artificial Intelligence, M. A. Boden, Ed., 2 ed., Handbook of Perception and Cognition, San Diego, CA: Academic Press, 1996, pp. 89-134.
  • S. Zilberstein and S. J. Russell, "Approximate Reasoning Using Anytime Algorithms," in Imprecise and Approximate Computation, S. Natarajan, Ed., Kluwer International Series in Engineering and Computer Science: Real-Time Systems, Vol. 318, Norwell, MA: Kluwer Academic Publishers, 1995, pp. 43-62.
  • S. Dzeroski, S. Muggleton, and S. J. Russell, "PAC-Learnability of Constrained, Nonrecursive Logic Programs," in Computational Learning Theory and Natural Learning Systems, Volume III: Selecting Good Models, T. Petsche, S. J. Hanson, and J. Shavlik, Eds., Vol. 3, Cambridge, MA: MIT Press, 1995, pp. 241-255.
  • S. J. Russell, "Prior Knowledge and Autonomous Learning," in Toward Learning Robots, W. Van De Velde, Ed., Bradford Books, Cambridge, MA: MIT Press, 1993, pp. 145-159.
  • S. Dzeroski, S. Muggleton, and S. J. Russell, "Learnability of constrained logic programs," in Machine Learning: Proc. European Conf. (ECML-1993), P. B. Brazdil, Ed., Lecture Notes in Artificial Intelligence, Vol. 667, Berlin, Germany: Springer-Verlag, 1993, pp. 342-347.
  • S. J. Russell and D. Subramanian, "On provably RALPHs [Rational Agents with Limited Performance Hardware]," in Computational Learning and Cognition: Proc. 3rd NEC Research Symp. (NEC 1992), E. B. Baum, Ed., Philadelphia, PA: Society for Industrial and Applied Mathematics, 1993, pp. 197-216.
  • S. J. Russell and E. Wefald, "Principles of Metareasoning," in Knowledge Representation, R. J. Brachman, H. J. Levesque, and R. Reiter, Eds., Bradford Book, Cambridge, MA: MIT Press, 1992, pp. 361-395.
  • S. J. Russell and B. N. Grosof, "Declarative Bias: An Overview," in Change of Representation and Inductive Bias: Proc. 1st Intl. Workshop, D. P. Benjamin, Ed., Springer International Series in Engineering and Computer Science, Vol. 87, Norwell, MA: Kluwer Academic Publishers, 1990.
  • S. J. Russell and D. Subramanian, "Mutual constraints on representation and inference," in Machine Learning, Meta-Reasoning, and Logics: Proc. Intl. Workshop, P. B. Brazdil and K. Konolige, Eds., Springer International Series in Engineering and Computer Science, Vol. 82, Norwell, MA: Kluwer Academic Publishers, 1990, pp. 85-106.
  • S. J. Russell and B. N. Grosof, "A sketch of autonomous learning using declarative bias," in Machine Learning, Meta-Reasoning, and Logics: Proc. Intl. Workshop, P. B. Brazdil and K. Konolige, Eds., Springer International Series in Engineering and Computer Science, Vol. 82, Norwell, MA: Kluwer Academic Publishers, 1990.
  • B. N. Grosof and S. J. Russell, "Shift of bias as non-monotonic reasoning," in Machine Learning, Meta-Reasoning, and Logics: Proc. Intl. Workshop, P. B. Brazdil and K. Konolige, Eds., Springer International Series in Engineering and Computer Science, Vol. 82, Norwell, MA: Kluwer Academic Publishers, 1990.
  • T. R. Davies and S. J. Russell, "A Logical Approach to Reasoning by Analogy," in Readings in Machine Learning, J. W. Shavlik and T. G. Dietterich, Eds., Morgan Kaufmann Machine Learning Series, San Mateo, CA: Morgan Kaufmann, 1990, pp. 657-663.
  • S. J. Russell, "Analogy by Similarity," in Analogical Reasoning: Perspectives of Artificial Intelligence, Cognitive Science, and Philosophy, D. H. Helman, Ed., Synthese Library, Vol. 197, Berlin, Germany: Springer-Verlag/Reidel, 1988, pp. 16 pg.

Articles in journals or magazines

Articles in conference proceedings

  • B. Marthi, S. J. Russell, and J. Wolfe, "Angelic hierarchical planning: Optimal and online algorithms," in Proc. 18th Intl. Conf. on Automated Planning and Scheduling (ICAPS 2008), J. Rintanen, B. Nebel, J. C. Beck, and E. Hansen, Eds., Menlo Park, CA: AAAI Press, 2008, pp. 222-231.
  • N. Aleks, S. J. Russell, M. G. Madden, K. Staudenmayer, M. Cohen, D. Morabito, and G. Manley, "Probabilistic modeling of sensor artifacts in critical care," in Proc. ICML-2008 Workshop on Machine Learning for Health-Care Applications, 2008, pp. 8 pg.
  • G. Lawrence and S. J. Russell, "Improving gradient estimation by incorporating sensor data," in Proc. 24th Conf. on Uncertainty in Artificial Intelligence (UAI-2008), D. A. McAllester and P. Myllymaki, Eds., Arlington, VA: AUAI Press, 2008, pp. 375-382.
  • J. Wolfe and S. J. Russell, "Exploiting belief state structure in graph search," in Proc. ICAPS 2007 Workshop on Planning in Games, Menlo Park, CA: AAAI Press, 2007, pp. 8 pg.
  • B. Marthi, S. J. Russell, and J. Wolfe, "Angelic semantics for high-level actions," in Proc. 17th Intl. Conf. on Automated Planning and Scheduling (ICAPS 2007), M. S. Boddy, M. Fox, and S. Thiebaux, Eds., Menlo Park, CA: AAAI Press, 2007, pp. 232-239.
  • B. Milch and S. J. Russell, "General-purpose MCMC inference over relational structures," in Proc. 22nd Conf. on Uncertainty in Artificial Intelligence (UAI-2006), Arlington, VA: AUAI Press, 2006, pp. 10 pg.
  • B. Marthi, S. J. Russell, and D. Andre, "A compact, hierarchical Q-function decomposition," in Proc. 22nd Conf. on Uncertainty in Artificial Intelligence (UAI-2006), Arlington, VA: AUAI Press, 2006, pp. 9 pg.
  • T. K. S. Kumar and S. J. Russell, "On some tractable cases of logical filtering," in Proc. 16th Intl. Conf. on Automated Planning and Scheduling (ICAPS 2006), D. Long, S. F. Smith, D. Borrajo, and L. McCluskey, Eds., Menlo Park, CA: AAAI Press, 2006, pp. 83-92.
  • B. Milch, B. Marthi, S. J. Russell, D. Sontag, D. L. Ong, and A. Kolobov, "BLOG: Probabilistic models with unknown objects," in Probabilistic, Logical and Relational Learning -- Towards a Synthesis, L. De Raedt, T. G. Dietterich, L. Getoor, and S. Muggleton, Eds., Dagstuhl Seminar Proceedings, Vol. 05051, Schloss Dagstuhl, Germany: IBFI, 2006, pp. 6 pg.
  • B. Milch, B. Marthi, S. J. Russell, D. Sontag, D. L. Ong, and A. Kolobov, "BLOG: Probabilistic models with unknown objects," in Proc. 19th Intl. Joint Conf. on Artificial Intelligence (IJCAI-2005), L. Pack Kaelbling and A. Saffiotti, Eds., Rochester Hills, MI: IJCAI, Inc., 2005, pp. 1352-1359.
  • B. Marthi, S. J. Russell, D. Latham, and C. Guestrin, "Concurrent hierarchical reinforcement learning," in Proc. 19th Intl. Joint Conf. on Artificial Intelligence (IJCAI-2005), L. Pack Kaelbling and A. Saffiotti, Eds., Rochester Hills, MI: IJCAI, Inc., 2005, pp. 779-785.
  • S. J. Russell and J. Wolfe, "Efficient belief-state AND-OR search, with application to Kriegspiel," in Proc. 19th Intl. Joint Conf. on Artificial Intelligence (IJCAI-2005), L. Pack Kaelbling and A. Saffiotti, Eds., Rochester Hills, MI: IJCAI, Inc., 2005, pp. 278-285.
  • B. Marthi, S. J. Russell, and D. Latham, "Writing Stratagus-playing agents in concurrent ALisp," in Reasoning, Representation, and Learning in Computer Games: Proc. of the IJCAI-2005 Workshop, D. W. Aha, H. Munoz-Avila, and M. van Lent, Eds., Washington, DC: Naval Research Laboratory, 2005, pp. 67-71.
  • B. Milch, B. marthi, D. Sontag, S. J. Russell, D. Ong, and A. Kolobov, "Approximate inference for infinite contingent Bayesian networks," in Proc. 10th Intl. Workshop on Artificial Intelligence and Statistics (AISTATS 2005), R. G. Cowell and Z. Ghahramani, Eds., The Society for Artificial Intelligence and Statistics, 2005, pp. 238-245.
  • S. Oh, S. J. Russell, and S. S. Sastry, "Markov chain Monte Carlo data association for general multiple-target tracking problems," in Proc. 43rd IEEE Conf. on Decision and Control (CDC 2004), Vol. 1, Piscataway, NJ: IEEE Press, 2004, pp. 735-742.
  • E. P. Xing, M. Jordan, and S. J. Russell, "Graph partition strategies for generalized mean field inference," in Proc. 20th Conf. on Uncertainty in Artificial Intelligence (UAI-2004), M. Chickering and J. Halpern, Eds., Arlington, VA: AUAI Press, 2004, pp. 602-610.
  • B. Marthi, D. Latham, C. Guestrin, and S. J. Russell, "Concurrent hierarchical reinforcement learning," in Proc. AAAI-04 Workshop on Learning and Planning in Markov Processes -- Advances and Challenges, D. Pucci de Farias, S. Mannor, D. Precup, and G. Theocharous, Eds., Menlo Park, CA: AAAI Press, 2004, pp. 5 pg.
  • B. Milch, B. Marthi, and S. J. Russell, "BLOG: Relational modeling with unknown objects," in Proc. ICML-2004 Workshop on Statistical Relational Learning and Its Connections to Other Fields (SRL '04), 2004, pp. 7 pg.
  • B. Marthi, B. Milch, and S. J. Russell, "First-order probabilistic models for information extraction," in Proc. IJCAI-03 Workshop on Learning Statistical Models from Relational Data (SRL '03), 2003, pp. 8 pg.
  • S. J. Russell and A. Zimdars, "Q-decomposition for reinforcement learning agents," in Proc. 20th Intl. Conf. on Machine Learning (ICML-2003), T. Fawcett and N. Mishra, Eds., Menlo Park, CA: AAAI Press, 2003, pp. 656-663.
  • E. P. Xing, M. Jordan, and S. J. Russell, "A generalized mean field algorithm for variational inference in exponential families," in Proc. 19th Conf. on Uncertainty in Artificial Intelligence (UAI-2003), C. Meek and U. Kjaerulff, Eds., San Francisco, CA: Morgan Kaufmann, 2003, pp. 583-591.
  • G. Lawrence, N. J. Cowan, and S. J. Russell, "Efficient gradient estimation for motor control learning," in Proc. 19th Conf. on Uncertainty in Artificial Intelligence (UAI-2003), C. Meek and U. Kjaerulff, Eds., San Francisco, CA: Morgan Kaufmann, 2003, pp. 354-361.
  • E. Amir and S. J. Russell, "Logical filtering," in Proc. 18th Intl. Joint Conf. on Artificial Intelligence (IJCAI-2003), G. Gottlob and T. Walsh, Eds., San Francisco, CA: Morgan Kaufmann, 2003, pp. 75-82.
  • E. Amir and S. J. Russell, "Temporal logical filtering," in Proc. 6th Intl. Symp. on Logical Formalizations of Commonsense Reasoning, P. Doherty, J. McCarthy, and M. Williams, Eds., AAAI Spring Symposium Series, Menlo Park, CA: AAAI Press, 2003.
  • M. Shilman, H. Pasula, S. J. Russell, and A. R. Newton, "Statistical visual language models for ink parsing," in Proc. 2002 AAAI Spring Symp. on Sketch Understanding, R. Davis, J. Landay, and T. Stahovich, Eds., Menlo Park, CA: AAAI Press, 2002, pp. 126-132.
  • D. Andre and S. J. Russell, "State abstraction for programmable reinforcement learning agents," in Proc. 18th National Conf. on Artificial Intelligence (AAAI-2002), R. Dechter, M. Kearns, and R. Sutton, Eds., Menlo Park, CA: AAAI Press, 2002, pp. 119-125.
  • B. Marthi, H. Pasula, S. J. Russell, and Y. Peres, "Decayed MCMC filtering," in Proc. 18th Conf. on Uncertainty in Artificial Intelligence (UAI-2002), A. Darwiche and N. Friedman, Eds., San Francisco, CA: Morgan Kaufmann, 2002, pp. 319-326.
  • N. de Freitas, P. A. d. F. R. Hojen-Sorensen, M. Jordan, and S. J. Russell, "Variational MCMC," in Proc. 17th Conf. on Uncertainty in Artificial Intelligence (UAI-2001), J. S. Breese and D. Koller, Eds., San Francisco, CA: Morgan Kaufmann, 2001, pp. 120-127.
  • N. C. Oza and S. J. Russell, "Experimental comparisons of online and batch versions of bagging and boosting," in Proc. 7th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining (KDD-2001), New York, NY: The Association for Computing Machinery, Inc., 2001, pp. 359-364.
  • H. Pasula and S. J. Russell, "Approximate inference for first-order probabilistic languages," in Proc. 17th Intl. Joint Conf. on Artificial Intelligence (IJCAI-2001), B. Nebel, Ed., Vol. 1, San Francisco, CA: Morgan Kaufmann, 2001, pp. 741-748.
  • S. J. Russell, "Identity uncertainty," in Proc. Joint 9th IFSA World Congress and 20th NAFIPS Intl. Conf., M. H. Smith, W. A. Gruver, and L. O. Hall, Eds., Vol. 2, Piscataway, NJ: IEEE Press, 2001, pp. 1056-1061.
  • N. C. Oza and S. J. Russell, "Online bagging and boosting," in Proc. 8th Intl. Workshop on Artificial Intelligence and Statistics (AISTATS 2001), T. Jaakkola and T. Richardson, Eds., San Francisco, CA: Morgan Kaufmann, 2001, pp. 105-112.
  • A. Doucet, N. de Freitas, K. P. Murphy, and S. J. Russell, "Rao-Blackwellised particle filtering for dynamic Bayesian networks," in Proc. 16th Conf. on Uncertainty in Artificial Intelligence (UAI-2000), C. Boutilier and M. Goldszmidt, Eds., San Francisco, CA: Morgan Kaufmann, 2000, pp. 176-183.
  • A. Y. Ng and S. J. Russell, "Algorithms for inverse reinforcement learning," in Proc. 17th Intl. Conf. on Machine Learning (ICML-2000), P. Langley, Ed., San Francisco, CA: Morgan Kaufmann, 2000, pp. 663-670.
  • V. A. Papavassiliou and S. J. Russell, "Convergence of reinforcement learning with general function approximators," in Proc. 16th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1999), T. Dean, Ed., Vol. 2, San Francisco, CA: Morgan Kaufmann, 1999, pp. 748-757.
  • H. Pasula, S. J. Russell, M. Ostland, and Y. Ritov, "Tracking many objects with many sensors," in Proc. 16th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1999), T. Dean, Ed., Vol. 2, San Francisco, CA: Morgan Kaufmann, 1999, pp. 1160-1171.
  • A. Y. Ng, D. Harada, and S. J. Russell, "Policy invariance under reward transformations: Theory and application to reward shaping," in Proc. 16th Intl. Conf. on Machine Learning (ICML-1999), I. Bratko and S. Dzeroski, Eds., San Francisco, CA: Morgan Kaufmann, 1999, pp. 278-287.
  • D. Harada and S. J. Russell, "Learning search strategies (Extended Abstract)," in Proc. AAAI Spring Symp. on Search Techniques for Problem Solving under Uncertainty and Incomplete Information, W. Zhang and S. Koenig, Eds., Menlo Park, CA: AAAI Press, 1999, pp. 5 pg.
  • G. Zweig and S. J. Russell, "Probabilistic modeling with Bayesian networks for automatic speech recognition," in Proc. 5th Intl. Conf. on Spoken Language Processing (ICSLP-1998), R. H. Mannell and J. Robert-Ribes, Eds., Vol. 7, Canberra, ACT, Australia: Australian Speech Science and Technology Association, Inc., 1998, pp. 3011-3014.
  • N. Friedman, K. Murphy, and S. J. Russell, "Learning the structure of dynamic probabilistic networks," in Proc. 14th Conf. on Uncertainty in Artificial Intelligence (UAI-1998), G. Cooper and S. Moral, Eds., San Francisco, CA: Morgan Kaufmann, 1998, pp. 139-147.
  • R. Dearden, N. Friedman, and S. J. Russell, "Bayesian Q-learning," in Proc. 15th National Conf. on Artificial Intelligence (AAAI-1998), Menlo Park, CA: AAAI Press, 1998, pp. 761-768.
  • G. Zweig and S. J. Russell, "Speech recognition with dynamic Bayesian networks," in Proc. 15th National Conf. on Artificial Intelligence (AAAI-1998), Menlo Park, CA: AAAI Press, 1998, pp. 173-180.
  • N. Friedman, K. Murphy, and S. J. Russell, "Learning the structure of dynamic probabilistic networks," in Proc. Conf. on Automated Learning and Discovery (CONALD 1998), 1998.
  • N. Friedman and S. J. Russell, "Image segmentation in video sequences: A probabilistic approach," in Proc. 13th Conf. on Uncertainty in Artificial Intelligence (UAI-1997), D. Geiger and P. P. Shenoy, Eds., San Francisco, CA: Morgan Kaufmann, 1997, pp. 175-181.
  • T. Huang and S. J. Russell, "Object identification in a Bayesian context (Distinguished Paper Award)," in Proc. 15th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1997), Vol. 2, San Francisco, CA: Morgan Kaufmann, 1997, pp. 1276-1282.
  • J. Binder, K. Murphy, and S. J. Russell, "Space-efficient inference in dynamic probabilistic networks," in Proc. 15th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1997), Vol. 2, San Francisco, CA: Morgan Kaufmann, 1997, pp. 1292-1296.
  • N. Friedman, M. Goldszmidt, D. Heckerman, and S. J. Russell, "Challenge: What is the impact of Bayesian networks on learning?," in Proc. 15th Intl. Joint Conf. Artificial Intelligence (IJCAI-1997), Vol. 1, San Francisco, CA: Morgan Kaufmann, 1997, pp. 10-15.
  • J. Forbes, T. Huang, K. Kanazawa, and S. J. Russell, "The BATmobile: Towards a Bayesian automated taxi," in Proc. 14th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1995), San Francisco, CA: Morgan Kaufmann, 1995, pp. 1878-1885.
  • S. J. Russell, J. Binder, D. Koller, and K. Kanazawa, "Local learning in probabilistic networks with hidden variables," in Proc. 14th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1995), Vol. 2, San Francisco, CA: Morgan Kaufmann, 1995, pp. 1146-1152.
  • R. Parr and S. J. Russell, "Approximating optimal policies for partially observable stochastic domains," in Proc. 14th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1995), Vol. 2, San Francisco, CA: Morgan Kaufmann, 1995, pp. 1088-1094.
  • S. J. Russell, "Rationality and intelligence (Invited Paper) (Computers and Thought Award)," in Proc. 14th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1995), Vol. 1, San Francisco, CA: Morgan Kaufmann, 1995, pp. 950-960.
  • K. Kanazawa, D. Koller, and S. J. Russell, "Stochastic simulation algorithms for dynamic probabilistic networks," in Proc. 11th Conf. on Uncertainty in Artificial Intelligence (UAI-1995), P. Besnard and S. Hanks, Eds., San Francisco, CA: Morgan Kaufmann, 1995, pp. 346-351.
  • S. Davies and S. J. Russell, "NP-completeness of searches for smallest possible feature sets," in Proc. AAAI Fall Symp. on Relevance, R. Greiner and D. Subramanian, Eds., Menlo Park, CA: AAAI Press, 1994, pp. 41-43.
  • S. J. Russell and P. Norvig, "A modern, agent-oriented approach to AI instruction," in Proc. AAAI Fall Symp. on Improving Instruction of Introductory Artificial Intelligence, M. Hearst, Ed., Menlo Park, CA: AAAI Press, 1994, pp. 15-18. [abstract]
  • D. Koller, J. Weber, T. Huang, J. Malik, G. Ogasawara, B. Rao, and S. J. Russell, "Towards robust automatic traffic scene analysis in real-time," in Proc. 12th IAPR Intl. Conf. on Pattern Recognition--Conf. A: Computer Vision and Image Processing (IAPR 1994), Vol. 1, Los Alamitos, CA: IEEE Computer Society, 1994, pp. 126-131.
  • T. Huang, D. Koller, J. Malik, G. H. Ogasawara, B. Rao, S. J. Russell, and J. Weber, "Automatic symbolic traffic scene analysis using belief networks," in Proc. 12th National Conf. on Artificial Intelligence (AAAI-1994), Vol. 2, Menlo Park, CA: AAAI Press, 1994, pp. 966-972.
  • J. Tash and S. J. Russell, "Control strategies for a stochastic planner," in Proc. 12th National Conf. on Artificial Intelligence (AAAI-1994), Vol. 2, Menlo Park, CA: AAAI Press, 1994, pp. 1079-1085.
  • S. J. Russell, D. Subramanian, and R. Parr, "Provably bounded optimal agents," in Proc. 13th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1993), R. Bajcsy, Ed., Vol. 1, San Mateo, CA: Morgan Kaufmann, 1993, pp. 338-344.
  • S. Zilberstein and S. J. Russell, "Anytime sensing, planning, and action: A practical model for robot control," in Proc. 13th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1993), R. Bajcsy, Ed., Vol. 2, San Mateo, CA: Morgan Kaufmann, 1993, pp. 1402-1407.
  • G. H. Ogasawara and S. J. Russell, "Planning using multiple execution architectures," in Proc. 13th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1993), R. Bajcsy, Ed., Vol. 2, San Mateo, CA: Morgan Kaufmann, 1993, pp. 1394-1401.
  • T. Huang, G. Ogasawara, and S. J. Russell, "Symbolic traffic scene analysis using belief networks," in Proc. 1993 AAAI Workshop on AI in Intelligent Vehicle Highway Systems, Y. Sekine, Ed., Menlo Park, CA: AAAI Press, 1993.
  • B. Barbour and S. J. Russell, "Experiments in adaptive indexing for logic programming," in Proc. ICML-93 Workshop on Knowledge Compilation and Speed-up Learning, 1993.
  • R. Musick, J. Catlett, and S. J. Russell, "Decision theoretic subsampling for induction on large databases," in Proc. 10th Intl. Conf. on Machine Learning (ICML-1993), San Mateo, CA: Morgan Kaufmann, 1993, pp. 212-219.
  • S. J. Russell and D. Subramanian, "Constructing bounded optimal systems," in Proc. 1993 AAAI Spring Symp. on AI and NP-Hard Problems, H. Hirsh and J. Crawford, Eds., Menlo Park, CA: AAAI Press, 1993.
  • G. H. Ogasawara and S. J. Russell, "Decision-theoretic planning with multiple execution architectures," in Proc. 1993 AAAI Spring Symp. on Foundations of Automatic Planning: The Classical Approach and Beyond, A. Lansky, Ed., Menlo Park, CA: AAAI Press, 1993.
  • S. Zilberstein and S. J. Russell, "Constructing utility-driven real-time systems using anytime algorithms," in Proc. 1st IEEE Workshop on Imprecise and Approximate Computation, Washington, DC: IEEE Computer Society, 1992, pp. 6-10.
  • S. Zilberstein and S. J. Russell, "Control of mobile robots using anytime computation," in Proc. 1992 AAAI Fall Symp. on Applications of Artificial Intelligence to Real-World Autonomous Mobile Robots, E. Gat and M. Slack, Eds., Menlo Park, CA: AAAI Press, 1992.
  • S. Dzeroski, S. Muggleton, and S. J. Russell, "PAC-learnability of constrained, nonrecursive logic programs," in Proc. 3rd Intl. Workshop on Computational Learning Theory and Natural Learning Systems (CLNL-1992), 1992.
  • S. J. Russell, "Efficient memory-bounded search methods," in Proc. 10th European Conf. on Artificial Intelligence (ECAI-1992), B. Neumann, Ed., New York, NY: John Wiley and Sons, Inc., 1992, pp. 1-5.
  • S. Zilberstein and S. J. Russell, "Reasoning about optimal allocation of time using conditional performance profiles," in Proc. AAAI-92 Workshop on Implementing Temporal Reasoning, M. Boddy, Ed., 1992.
  • S. Dzeroski, S. Muggleton, and S. J. Russell, "PAC-learnability of determinate logic programs," in Proc. 5th Annual Workshop on Computational Learning Theory (COLT 1992), New York, NY: The Association for Computing Machinery, Inc., 1992, pp. 128-135.
  • R. Musick and S. J. Russell, "How long will it take?," in Proc. 10th National Conf. Artificial Intelligence (AAAI-1992), W. R. Swartout, Ed., Menlo Park, CA: AAAI Press, 1992, pp. 466-471.
  • S. Zilberstein and S. J. Russell, "Efficient resource-bounded reasoning in AT-RALPH," in Proc. 1st Intl. Conf. on Artificial Intelligence Planning Systems (AIPS-1992), J. Hendler, Ed., San Mateo, CA: Morgan Kaufmann, 1992, pp. 260-266.
  • S. J. Russell, "An architecture for bounded rationality," in Proc. IJCAI-91 Workshop on Theoretical and Practical Design for Rational Agents, 1991.
  • S. J. Russell and S. Zilberstein, "Composing real-time systems," in Proc. 12th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1991), J. Mylopoulos and R. Reiter, Eds., Vol. 1, San Mateo, CA: Morgan Kaufmann, 1991, pp. 212-217.
  • S. J. Russell, "An architecture for bounded rationality," in Proc. 1991 AAAI Spring Symp. on Integrated Architectures for Intelligent Agents, Menlo Park, CA: AAAI Press, 1991.
  • O. Hansson, A. Mayer, and S. J. Russell, "Decision-theoretic planning in BPS," in Proc. 1990 AAAI Spring Symp. on Planning in Uncertain Environments, 1990.
  • S. Srinivas, S. J. Russell, and A. M. Agogino, "Automated construction of sparse Bayesian networks from unstructured probabilistic models and domain information," in Uncertainty in Artificial Intelligence 5: Proc. Annual Conf. (UAI-1989), M. Henrion, R. D. Shachter, L. N. Kanal, and J. F. Lemmer, Eds., Amsterdam, The Netherlands: North-Holland Publishing Co., 1990, pp. 295-308.
  • S. J. Russell, "Execution architectures and compilation," in Proc. 11th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1989), N. S. Sridharan, Ed., Vol. 1, San Mateo, CA: Morgan Kaufmann, 1989, pp. 15-20.
  • S. J. Russell and E. Wefald, "On optimal game-tree search using rational meta-reasoning," in Proc. 11th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1989), N. S. Sridharan, Ed., Vol. 1, San Mateo, CA: Morgan Kaufman, 1989, pp. 334-340.
  • B. N. Grosof and S. J. Russell, "Declarative bias for structural domains," in Proc. 6th Intl. Conf. on Machine Learning (ICML-1989), A. M. Segre, Ed., San Mateo, CA: Morgan Kaufmann, 1989, pp. 480-482.
  • E. Wefald and S. J. Russell, "Adaptive learning of decision-theoretic search control knowledge," in Proc. 6th Intl. Conf. on Machine Learning (ICML-1989), A. M. Segre, Ed., San Mateo, CA: Morgan Kaufmann, 1989, pp. 408-411.
  • S. J. Russell and E. Wefald, "Principles of metareasoning," in Proc. 1st Intl. Conf. on Principles of Knowledge Representation and Reasoning (KR 1989), R. J. Brachman, H. J. Levesque, and R. Reiter, Eds., San Mateo, CA: Morgan Kaufmann, 1989, pp. 400-411.
  • E. Wefald and S. J. Russell, "Estimating the value of computation: The case of real-time search," in Working Notes of the 1989 AAAI Spring Symp. on AI and Limited Rationality, 1989, pp. 106-110.
  • A. M. Agogino, R. Guha, and S. J. Russell, "Sensor fusion using influence diagrams and reasoning by analogy: Application to milling machine monitoring and control," in Artificial Intelligence in Engineering: Proc. 3rd Intl. Conf., J. S. Gero, Ed., Amsterdam, The Netherlands: Elsevier Science Publishers, 1988.
  • S. J. Russell, "Tree-structured bias," in Proc. 7th National Conference on Artificial Intelligence (AAAI-1988), Menlo Park, CA: AAAI Press/MIT Press, 1988, pp. 641-645.
  • M. S. Braverman and S. J. Russell, "IMEX: Overcoming intactability in explanation based learning," in Proc. 7th National Conference on Artificial Intelligence (AAAI-1988), Menlo Park, CA: AAAI Press/MIT Press, 1988, pp. 575-579.
  • A. M. Agogino, R. Guha, and S. J. Russell, "Sensor fusion using influence diagrams and reasoning by analogy: Application to milling machine monitoring and control," in Artificial Intelligence in Engineering: Diagnosis and Learning, J. S. Gero, Ed., Vol. 3, Southampton, UK: WIT Press, 1988.
  • M. S. Braverman and S. J. Russell, "Boundaries of operationality," in Proc. 5th Intl. Conf. on Machine Learning (ICML-1988), J. E. Laird, Ed., San Mateo, CA: Morgan Kaufmann, 1988, pp. 221-234.
  • S. J. Russell and E. Wefald, "Multi-level decision-theoretic search," in Proc. AAAI Spring Symp. on Computer Game-Playing, 1988, pp. 3-7.
  • M. Braverman and S. J. Russell, "Explanation-based learning in complex domains," in Proc. AAAI Spring Symp. on Explanation-Based Learning, G. F. DeJong, Ed., 1988.
  • T. R. Davies and S. J. Russell, "A logical approach to reasoning by analogy," in Proc. 10th Intl. Joint Conf. on Artificial Intelligence (IJCAI-1987), J. McDermott, Ed., Vol. 1, San Mateo, CA: Morgan Kaufmann, 1987, pp. 264-270.
  • S. J. Russell and B. N. Grosof, "A declarative approach to bias in concept learning," in Proc. 6th National Conf. on Artificial Intelligence (AAAI-1987), K. S. H. Forbus, Ed., San Mateo, CA: Morgan Kaufmann, 1987, pp. 505-510.
  • S. J. Russell, "Analogy and single-instance generalization," in Proc. 4th Intl. Workshop on Machine Learning, P. Langley, Ed., San Mateo, CA: Morgan Kaufmann, 1987, pp. 390-397.
  • S. J. Russell, "A quantitative analysis of analogy by similarity," in Proc. 5th National Conf. on Artificial Intelligence (AAAI-1986), Vol. 1, San Mateo, CA: Morgan Kaufmann, 1986, pp. 284-288.
  • S. J. Russell, "Preliminary steps toward the automation of induction," in Proc. 5th National Conf. on Artificial Intelligence (AAAI-1986), Vol. 1, San Mateo, CA: Morgan Kaufmann, 1986, pp. 477-484.

Conference proceedings (edited)

  • A. Prieditis and S. J. Russell, Eds., Machine Learning: Proceedings of the 12th International Conference, San Francisco, CA: Morgan Kaufmann, 1995.

Technical Reports

Talks or presentations

Ph.D. Theses

  • S. J. Russell, "Analogical and Inductive Reasoning," Stanford University, Department of Computer Science, Dec. 1986.