Judy Goldsmith's Papers, By Topic

  • Applications/Models
  • Complexity of MDP, POMDP, and Bayesian Network Problems
  • Computational Complexity
  • Computational Learning Theory
  • Computational Social Choice
  • Computer Science Education
  • Editorials
  • Hedonic Games
  • Heuristics for MDPs/POMDPs/BNs
  • Preferences
  • Semistructured Probabilistic Databases
  • Technical Writing
  • The Bayesian Advisor Project
  • The Welfare-to-Work Project
  • Computer Vision
  • Other

  • Computer Science Education

    Ethical Considerations in Artificial Intelligence Courses
    Emanuelle Burton, Judy Goldsmith, Sven Koenig, Benjamin Kuipers, Nicholas Mattei, and Toby Walsh
    arXiv:1701.07769, also to appear: AI Magazine Summer 2017.

    Why Teaching Ethics to AI Practitioners is Important
    Judy Goldsmith, Emanuelle Burton
    Proc. AAAI 2017.

    Using “The Machine Stops” for Teaching Ethics in Artificial Intelligence and Computer Science
    Emanuelle Burton, Judy Goldsmith, and Nicholas Mattei
    Proc. AAAI Workshop on Ethics and AI 2016.

    Adventures with Prolog: Entering the Dungeon Lord’s Lair
    Thomas E. Allen, Judy Goldsmith, Nahom Muluney, and Andrew A. Ward
    Proc. AAAI Education Track, 2016.
    Link to Assignment at EAAI Model Assignment Page

    Teaching AI Ethics Using Science Fiction
    Emanuelle Burton, Judy Goldsmith, and Nicholas Mattei
    Ethics & AI Workshop at AAAI 2015.

    Lessons Learned from Development of a Software Tool to Support Academic Advising
    Nicholas Mattei, Thomas Dodson, Joshua T. Guerin, Judy Goldsmith, Joan M. Mazur
    Proc. American Society for Engineering Education Zone 1 Conference, 2014.

    Fiction as an Introduction to AI Research
    Judy Goldsmith and Nicholas Mattei
    ACM Transactions on Computing Education (TOCE), Volume 14 Issue 1, March 2014.

    Online Discussions: Improving Education in CS?
    Radu Paul Mihail, Beth Rubin, and Judy Goldsmith
    Proc. SIGCSE 2014.

    Teaching Graphics for Games using Microsoft XNA
    Radu Paul Mihail, Judy Goldsmith, Nathan Jacobs and Jerzy W. Jaromczyk
    Proc. CGAMES , 2013.

    Science Fiction as an Introduction to AI Research
    Judy Goldsmith and Nicholas Mattei
    Proc. AAAI 2011, Educational Advances in AI Track, 2011.

    Hedonic Games

    Stability in Role Based Hedonic Games
    Matthew Spradling and Judy Goldsmith
    Proc. FLAIRS 2015.

    Roles and Teams Hedonic Game
    Matthew Spradling, Judy Goldsmith, Xudong Liu, Chandrima Dadi, and Zhiyu Li
    Proc. Algorithmic Decision Theory, 2013.

    Applications/Models

    An English-Language Argumentation Interface for Explanation Generation with Markov Decision Processes in the Domain of Academic Advising
    Thomas Dodson, Nicholas Mattei, Joshua T. Guerin, and Judy Goldsmith,
    special issue, "Human Decision Making and Recommender Systems," ACM Transactions on Interactive Intelligent Systems, 2013.

    Introduction to the Special Issue on Bayesian Model Views
    Judy Goldsmith and Kathy Laskey
    International Journal of Approximate Reasoning, Special Issue on Bayesian Applicatio ns, Volume 51, Issue 2, Jan. 2010, pp. 165–166.
    Applications/Models

    Decision-theoretic Harmony: A First Step
    Liangrong Yi and Judy Goldsmith
    International Journal of Approximate Reasoning, Special Issue on Bayesian Applications, Volume 51, Issue 2, Jan. 2010,

    Planning for Welfare to Work
    Liangrong Yi, Raphael Finkel and Judy Goldsmith
    Proc. Florida AI Research Symposium (FLAIRS ’08), pp. 696–702.

    The Conference Paper Assignment Problem
    Judy Goldsmith and Robert H. Sloan
    Proc. AAAI Workshop on Preference Handling in AI, 2007.

    A Benchmark Model for Decision-Theoretic Planning with Constraints
    Kendra Renee Gehlbach, Brandon Laracuente, Cynthia Isenhour, Judy Goldsmith, Beth Goldstein and Mirosław Truszczyński
    The Fourth Bayesian Modelling Applications Workshop during UAI 2006.

    Factored MDP Elicitation and Plan Display
    Krol Kevin Mathias, Casey Lengacher, Derek Williams, Austin Cornett, Alex Dekhtyar and Judy Goldsmith
    ISDN, AAAI ’06.

    When Domains Require Modeling Adaptations
    Krol Kevin Mathias, Cynthia Isenhour, Alex Dekhtyar, Judy Goldsmith and Beth Goldstein
    The Fourth Bayesian Modelling Applications Workshop during UAI 2006.

    Adaptive decision support for planning under hard and soft constraints
    Alex Dekhtyar, Raphael Finkel, Judy Goldsmith, Beth Goldstein and Joan Mazur
    Proc. AAAI Spring Symposium on Decision Support in a Changing World, AAAI Press, 2005.

    Interactive Preferences and Decision-Theoretic Planning
    D. Williams, K. Bailey, A. Dekhtyar, R. Finkel, J. Goldsmith, B. Goldstein and J. Mazur
    Proc. IJCAI Workshop on Preference Handling, 2005.

    The Bayesian advisor project I: modeling academic advising
    Alexander Dekhtyar, Judy Goldsmith, Huazhi Li and Brett Young
    UK CS Dept. Tech Report 323-01.


    Complexity of MDP, POMDP, and Bayesian Network Problems

    Finding the k Best Policies
    Peng Dai and Judy Goldsmith
    Proc. 1st International Conference on Algorithmic Decision Theory, 2009.

    When plans distinguish Bayes nets
    Alex Dekhtyar, Jan Pearce and Judy Goldsmith
    International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (IJUFKS) Vol 11, Suppl, pp. 1-24, November 2003.

    Nonapproximability results for partially observable Markov decision processes
    C. Lusena, J. Goldsmith and M. Mundhenk
    Journal of AI Research 14: 83–103, 2001.

    When plans distinguish Bayes nets
    Alex Dekhtyar, Judy Goldsmith and Jan Pearce
    KI-2001 workshop ”Uncertainty in Artificial Intelligence”, September, 2001.

    The complexity of finite-horizon Markov decision process problems
    M. Mundhenk, C. Lusena, J. Goldsmith and E. Allender
    Journal of the ACM 47: (4), 681-720, July 2000.

    The complexity of model aggregation
    J. Goldsmith and R.H. Sloan
    Proc. AI, Planning and Scheduling (AIPS '00).

    More theory revision with queries
    J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
    Proc. 2000 ACM Symposium on Theory of Computing, May, 2000.

    Complexity issues in Markov decision processes
    Judy Goldsmith and Martin Mundhenk
    Proc. IEEE Conference on Computational Complexity 1998.

    The complexity of plan existence and evaluation in probabilistic domains
    M.L. Littman, M. Mundhenk and J. Goldsmith
    Journal of AI Research, 1998.
    Also appeared in: Proc. Conference on Uncertainty in AI, August 1997.

    The Computational Complexity of Probabilistic Planning
    M. Littman, J. Goldsmith and M. Mundhenk
    The Journal of AI Research, volume 9, pages 1–36, 1998.

    The complexity of deterministically observable finite-horizon Markov decision processes
    Judy Goldsmith, Christopher Lusena and Martin Mundhenk
    UK CS Department Technical Report 268-96.

    The complexity of unobservable finite-horizon Markov decision processes (extended abstract)
    M. Mundhenk, J. Goldsmith and E. Allender
    UK CS Department Technical Report 269-96.
    More recent version. A shorter version appeared in the Proc. MFCS '97.


    Computational Complexity

    The Complexity of Probabilistic Lobbying
    Gábor Erdélyi, Henning Fernau, Judy Goldsmith, Nicholas Mattei, Daniel Raible and Jörg Rothe
    Proc. 1st International Conference on Algorithmic Decision Theory, 2009.

    Complexity of DNF minimization and isomorphism testing for monotone formulas
    Judy Goldsmith, Matthias Hagen and Martin Mundhenk
    Information and Computation, Vol 206/6 pp 760-775, June 2008.
    Proc. Mathematical Foundations of Computer Science (MFCS ’05), Springer Lecture Notes in Computer Science, Vol. 3618, 2005.

    Competition Adds Complexity
    Martin Mundhenk and Judy Goldsmith
    Proc. Neural Information Processing Systems (NIPS 2007), pp. 561–568.

    Preferences and Domination
    J. Goldsmith
    Dagstuhl Electronic Proceedings, 2005.
    Dagstuhl Seminar Proceedings, Seminar 04421, 2004.

    Tally NP sets and easy census functions
    J. Goldsmith, M. Ogihara and J. Rothe
    Information and Computation 158: (1) 29-52 APR 10 2000.
    Proc. MFCS ’98, Springer-Verlag Lecture Notes in Computer Science 1450: 483-492, 1998.

    An algorithm for the class of pure implicational formulas
    J. Franco, J. Goldsmith, J. Schlipf, E. Speckenmeyer and R. Swaminathan
    Discrete Applied Mathematics 97: 89-106 OCT 15 1999.
    Also appeared in: Siena Workshop on Satisfiability, Università degli Studi di Siena, Siena, Italy, May, 1996.

    Downward separation fails catastrophically for limited nondeterminism classes
    Richard Beigel and Judy Goldsmith
    SIAM J. Comp. 5: 1998.
    Also appeared in: Proc. 10th Structure in Complexity Theory Conference (1994).

    L-printable sets
    L. Fortnow, J. Goldsmith, M. Levy and S. Mahaney
    SIAM J. Comp. 28: (1) 137-151 1998.
    Also appeared in: Proc. Conference on Computational Complexity (Formerly the Structure in Complexity Theory Conference) (May, 1996).

    Sharply bounded alternation and quasilinear time
    Stephen Bloch, Jonathan Buss and Judy Goldsmith
    Theory of Computing Systems (formerly Mathematical System Theory) 31: (2) 187-214 MAR-APR 1998.

    Limited Nondeterminism
    Judy Goldsmith, Matthew Levy and Martin Mundhenk
    UK CS Department Technical Report 267-96.
    Appeared without the appendix in the Complexity Theory Column of SIGACT News, June, 1996.

    Scalability and the isomorphism problem
    Judy Goldsmith and Steve Homer
    Information Processing Letters 57: (3) 137-143 FEB 12 1996.

    Sharply bounded alternation with P
    S. Bloch, J. Buss and J. Goldsmith
    Proc. DMTCS’96, Springer-Verlag Lecture Notes in Computer Science (1996).

    How hard are n2-hard problems?
    Stephen Bloch, Jonathan Buss and Judy Goldsmith
    SIGACT News 91 (1994), 83–85.

    A note on bi-immunity and p-closeness of p-cheatable sets in P/poly
    J. Goldsmith, D. Joseph and P. Young
    Journal of Computer System Science 46: (3) 349-362 JUN 1993.

    Nondeterminism within P
    J. Buss and J. Goldsmith
    SIAM Journal of Computing 22: (3) 560-572 JUN 1993.
    Also appeared in: Proceedings Symposium on Theoretical Computer Science, Springer-Verlag Lecture Notes in Computer Science #480 (1991), 348–359.

    Relativized isomorphisms of NP-complete sets
    J. Goldsmith and D. Joseph
    Computational Complexity, 186–205, 1993.

    Using self-reducibility to characterize polynomial time
    J. Goldsmith, D. Joseph and P. Young
    Information and Computation 104: (2) 288-308 JUN 1993.

    On the structure and complexity of infinite sets with minimal perfect hash functions
    J. Goldsmith, L. Hemachandra and K. Kunen
    Computational Complexity 2: 18–39, 1992.
    Also appeared in: Proceedings of the 11th Foundations of Software Technology and Theoretical Computer Science Conference, Springer-Verlag Lecture Notes in Computer Science 560: 212-223 1991.

    Near-testable sets
    J. Goldsmith, L. Hemachandra, D. Joseph and P. Young
    SIAM Journal of Computing, 20:3, 1991.

    Polynomial Isomorphisms and Near-Testable Sets
    J. Goldsmith
    PhD. Thesis, University of Wisconsin-Madison (1988). Also available as University of Wisconsin Technical Report # 816 (1989).

    Self-reducibility, near-testability, and p-cheatable sets: The effect of internal structure on the complexity of a set
    J. Goldsmith, D. Joseph and P. Young
    Proceedings of the Second Annual Structure in Complexity Theory Conference, IEEE Computer Society (1987), 50-60.

    Three results on the polynomial isomorphisms of sets
    J. Goldsmith, D. Joseph
    Proc. Twenty-seventh Foundations of Computer Science Conference, IEEE Computer Society (1986), 390-397.


    Computational Social Choice


    The Complexity of Campaigning
    Cory Siler, Luke Harold Miles, Judy Goldsmith
    Proc. Algorithmic Decision Theory 2017.

    Probabilistic Copeland Tournaments
    Sam Saarinen, Judy Goldsmith, and Craig Tovey
    Proc. AAMAS 2015.

    Voting with Rank Dependent Scoring Rules
    J\'er\^ome Lang, Judy Goldsmith, Nicholas Mattei and Patrice Perny
    EXPLORE Workshop at AAMAS; ComSoc '14, Proc. AAAI, 2014.

    Voting with CP-nets using a Probabilistic Preference Structure
    Cristina Cornelio, Umberto Grandi, Judy Goldsmith, Nicholas Mattei, Francesca Rossi and K. Brent Venable
    ComSoc 2014.

    The Complexity of Probabilistic Lobbying,
    G\'{a}bor Erd\'{e}lyi, Henning Fernau, Judy Goldsmith, Nicholas Mattei, Daniel Raible and Jörg Rothe,
    Discrete Optimization, (11)1-–21 2014.

    Algorithms, approximation, and empirical studies in behavioral and computational social choice-—Preface
    Judy Goldsmith and Jörg Rothe
    Annals of Mathematics and Artificial Intelligence, September 2013

    An Empirical Study of Voting Rules and Manipulation with Large Datasets,
    Nicholas Mattei, James Forshee, Judy Goldsmith
    ComSoc 2012.

    On the Complexity of Bribery and Manipulation in Tournaments with Uncertain Information
    Nicholas Mattei, Judy Goldsmith, and Andrew Klapper
    Florida AI Research Symposium (FLAIRS '12), 2012.

    Computational Learning Theory

    New Horn Revision Algorithms
    Judy Goldsmith and Robert H. Sloan
    Journal of Machine Learning Research, 6(Dec):1919–1938, 2005.

    Revision algorithms using queries: results and problems
    J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
    Proc. NIPS Foundations of Active Learning workshop, December, 2005.

    Theory revision with queries: results and problems
    J. Goldsmith, R.H. Sloan, B. Szörényi and G. Turán
    Proc. Workshop on Learning with Logics and Logics for Learning, Japan, 2005.

    Theory Revision with Queries: Horn, Read-once, and Parity Formulas
    J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
    Artificial Intelligence Journal 156: (2) 139–176, July 2004.

    New Revision Algorithms
    J. Goldsmith, R.H. Sloan, Balázs Szörényi and György Turán
    Proc. Conference on Algorithmic Learning Theory (ALT ’04), pp. 395 - 409, September, 2004.

    Theory Revision with Queries: DNF Formulas
    Judy Goldsmith, Robert H. Sloan and György Turán
    Machine Learning 47(2-3): 257-295, May/June 2002.

    Improved algorithms for theory revision with queries (extended abstract)
    J. Goldsmith and R.H. Sloan
    Proc. 2000 Conference on Computational Learning Theory, June, 2000.


    Editorial

    Editors’ introduction to the special issue on model views in Bayesian applications
    Judy Goldsmith and Kathy Laskey
    International Journal on Approximate Reasoning, to appear.

    Preference Handling for Artificial Intelligence
    Judy Goldsmith and Ulrich Junker
    AI Magazine, Winter, 2008.

    Crisis or opportunity?
    Judy Goldsmith
    in the Complexity Theory Column of SIGACT News 27, 1996.


    Heuristics for MDPs/POMDPs/BNs

    An English-Language Argumentation Interface for Explanation Generation with Markov Decision Processes in the Domain of Academic Advising,
    Thomas Dodson, Nicholas Mattei, Joshua T. Guerin, and Judy Goldsmith, special issue, "Human Decision Making and Recommender Systems," ACM Transactions on Interactive Intelligent Systems, 2013.

    Approximation of Lorenz-Optimal Solutions in Multiobjective Markov Decision Processes,
    Patrice Perny, Paul Weng, Judy Goldsmith, Josiah P. Hanna, Proc. UAI 2013.

    Topological Value Iteration Algorithms
    Peng Dai, Mausam, Dan Weld, and Judy Goldsmith
    Journal of Artificial Intelligence Research, Volume 42, pages 181--209, 2011.

    Natural Language Argumentation Interface for Explanation Generation in Markov Decision Processes
    Thomas Dodson, Nicholas Mattei, and Judy Goldsmith
    Proc. EXaCT Workshop, IJCAI 2011; Proc. Algorithmic Decision Theory, 2011.

    Ranking Policies in Discrete Markov Decision Processes
    Peng Dai and Judy Goldsmith
    Annals of Mathematics and Artificial Intelligence, 59(1): 107--123, 2010.

    Expediting RL by Using Graphical Structures
    Peng Dai, Alexander Strehl and Judy Goldsmith
    Proc. The 7th Internat’l Conference on Autonomous Agents and Multiagent Systems (AAMAS ’08), pp. 1325-1328.

    Multi-threaded BLAO* Algorithm
    Peng Dai and Judy Goldsmith
    FLAIRS 2007.

    Topological Value Iteration Algorithm for Markov Decision Processes
    Peng Dai and Judy Goldsmith
    Proc. IJCAI 2007.

    LAO*, RLAO* or BLAO*
    Peng Dai and Judy Goldsmith
    Proc. AAAI Workshop on Heuristic Search, Memory Based Heuristics and Their Applications, 2006.

    Bidirectional LAO*
    Kiran Bhuma and Judy Goldsmith
    First Indian International Conference on Artificial Intelligence, pp. 980–992, December, 2003.

    Genetic algorithms for approximating solutions to POMDPs
    C.Wells, C. Lusena and J. Goldsmith
    UK CS Dept Tech Report 290-99.

    My brain is full: When more memory helps
    C.D. Lusena, T. Li, S. Sittinger, C.A. Wells and Judy Goldsmith
    Proc. Uncertainty in AI, July, 1999.


    Preferences

    Uniform Random Generation and Dominance Testing for CP-Nets
    Thomas E. Allen, Judy Goldsmith, Hayden E. Justice, Nicholas Mattei, and Kayla Raines
    JAIR Volume 59, pages 771-813, 2017.

    Learning Tree Structured CP-Nets with Local Search
    Thomas E. Allen, Cory Siler, Judy Goldsmith
    FLAIRS May 2017.

    Generating CP-nets Uniformly at Random
    Thomas E.~Allen, Judy Goldsmith, Hayden E.~Justice, Nicholas Mattei, and Kayla Raines
    Proc. AAAI Technical Track, 2016.

    A Tool to Graphically Edit CP-nets
    Aidan Shafran, Sam Saarinen, and Judy Goldsmith
    Proc. AAAI Demo Track, 2016.

    Who is Watching You Eat?: a noir preferences thriller
    Judy Goldsmith, Nicholas Mattei and Robert Sloan
    AI Matters archive, Volume 1 Issue 4, June 2015, Pages 13-22, Summer 2015.

    Reasoning with PCP-nets in a Multi-agent Context
    Cristina Cornelio, Umberto Grandi, Judy Goldsmith, Nicholas Mattei, Francesca Rossi, K. Brent Venable
    Proc. AAMAS 2015.

    Who is Watching You Eat?
    Judy Goldsmith, Nicholas Mattei and Robert Sloan
    MPREF Workshop at AAAI 2014.

    A Model for Intransitive Preferences
    Sam Saarinen, Craig A. Tovey and Judy Goldsmith
    MPREF Workshop at AAAI 2014.

    Counting, Ranking, and Randomly Generating CP-nets
    Thomas E. Allen, Judy Goldsmith and Nicholas Mattei
    MPREF Workshop at AAAI 2014.

    Updates and Uncertainty in CP-nets,
    Cristina Cornelio, Judy Goldsmith, Nicholas Mattei, Francesca Rossi and Kristen Brent Venable,
    26th Australasian Joint Conference on Artificial Intelligence (AI '13), Dunedin, New Zealand, 2013.

    Learning CP-net Preferences Online from User Queries,
    Joshua T. Guerin, Thomas E. Allen, and Judy Goldsmith,
    Proc. Algorithmic Decision Theory 2013.

    "Putting Preferences into Computational Context,"
    Judy Goldsmith,
    commentary in Comparative Decision Making: Analysis and Support Across Disciplines and Applications,
    Oxford University Press, 2013.

    The computational complexity of dominance and consistency in CP-nets
    Judy Goldsmith, Jérôme Lang, Mirosław Truszczyński and Nic Wilson
    Journal of Artificial Intelligence Research, Volume 33, pages 403–432, 2008.
    Proc. 21st International Joint Conference on AI (IJCAI ’05).

    Preferences and Domination
    J. Goldsmith
    Dagstuhl Electronic Proceedings, 2005.
    Dagstuhl Seminar Proceedings, Seminar 04421, 2004.

    POET, The Online Preference Elicitation Tool
    James Royalty, Derek Williams, Robert Holland, Judy Goldsmith and Alex Dekhtyar
    Proc. AAAI Workshop on Preferences in AI and CP: A Symbolic Approach, July, 2002.


    Semistructured Probabilistic Databases

    Probabilistic Databases and their Applications
    Alex Dekhtyar, Tingjian Ge, and Judy Goldsmith, in Advances in Probabilistic Databases for Uncertain Information Management (editors Zongmin Ma and Li Yan), Springer-Verlag (in the series Studies in Fuzziness and Soft Computing), pp. 67--108.

    A Framework for Management of Semistructured Probabilistic Data
    Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
    Journal of Intelligent Information Systems 25:3, 2005.

    Building Bayes Nets with Semistructured Probabilistic DBMS
    Wenzhong Zhao, Alex Dekhtyar, Judy Goldsmith, Erik Jessup and Jiangyu Li
    GI-EMISA Forum (ISBN 1610-3351), 1:29-30, 2004.

    Databases for Interval Probabilities
    Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
    International Journal of Intelligent Systems, 19: (9) 789–815, September, 2004.

    Can Probabilistic Databases Help Elect Qualified Officials?
    Judy Goldsmith, Alex Dekhtyar and Wenzhong Zhao
    Proc. Florida AI Research Symposium, May, 2003.

    Representing Probabilistic Information in XML
    Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
    University of Kentucky Department of Computer Science Tech. Report 770-03 April, 2003.

    Query Algebra Operations for Interval Probabilities
    Wenzhong Zhao, Alex Dekhtyar and Judy Goldsmith
    Proc. 14th International Conference on Database and Expert Systems Applications, September, 2003. Available in Springer Lecture Notes in Computer Science 2736, pp. 527 - 536.

    Conditionalization for Interval Probabilities
    Alex Dekhtyar and Judy Goldsmith
    Proc. Workshop on Conditionals, Information, and Inference, May, 2002.

    Semistructured Probabilistic Databases
    A. Dekhtyar, S. Hawkes and J. Goldsmith
    Proc. Statistical and Scientific Database Management Systems, June, 2001.


    Technical Writing

    Write it Right
    Judy Goldsmith and Robert H. Sloan
    IEEE Professional Communication Society Newsletter

  • The Very Basics, Vol. 51, No. 8, Sept. 2007.
  • Relevant Forms of Technical Writing, Vol. 51, No. 10, Nov. 2007.
  • Reviews, Coauthorship, and Citations, Vol. 51, No. 11, Dec. 2007.
  • Several Matters of Mechanics, Vol. 52, No. 1, Jan. 2008.
  • Considerations for Experimental Work, Vol. 52, No.2, Feb. 2008.

  • The Bayesian Advisor Project

    The Academic Advising Planning Domain
    Joshua Guerin, Josiah Hanna, Libby Knouse, Nicholas Mattei and Judy Goldsmith
    ICAPS 2012 International Planning Competition Workshop, 2012.

    Natural Language Argumentation Interface for Explanation Generation in Markov Decision Processes
    Thomas Dodson, Nicholas Mattei, and Judy Goldsmith
    Proc. EXaCT Workshop, IJCAI 2011; Proc. Algorithmic Decision Theory, 2011.

    Constructing Dynamic Bayes Net Models of Academic Advising
    Joshua T. Guerin and Judy Goldsmith
    Proc. 8th Bayesian Modeling Applications Workshop, 2011.

    Efficiently Eliciting Many Probabilities Online
    Jiangyu Li, Alex Dekhtyar and Judy Goldsmith
    Tech Report, 2002.

    The Bayesian Advisor Project
    Alex Dekhtyar and Judy Goldsmith
    Tech Report, 2002.


    The Welfare-to-Work Project

    Planning for success: The interdisciplinary approach to building Bayesian models
    Alex Dekhtyar, Judy Goldsmith, Beth Goldstein, Krol Kevin Mathias and Cynthia Isenhour
    International Journal of Approximate Reasoning, Volume 50, Issue 3, March 2009, Pages 416–428, Special Section on Bayesian Modelling.

    Social Construction of Technology in the Welfare to Work Project
    Joan Mazur, Beth Goldstein and Judy Goldsmith
    UAI Workshop on Bayesian Applications, 2004.


    Computer Vision

    Real Time Gesture Recognition With 2 Kinect Sensors
    Radu Paul Mihail, Nathan Jacobs, Judy Goldsmith>
    16th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV), 2012.


    Other

    Uncertainty as the Source of Knowledge Transfer Opportunity
    Alexander Dekhtyar, Jane Hayes and Judy Goldsmith
    Proc. 1st International Workshop on Living with Uncertainties (IWLU01), 2007.

    Markov Indecision Processes: A Formal Model of Decision-Making Under Extreme Confusion
    Harry Q. Bovik, Judy Q. Goldsmith, Andrew Q. Klapper and Michael Q. Littman
    Journal of Machine Learning Gossip, 1(Apr):1-9, 2003.

    Public key cryptosystems with partial secrecy
    Judy Goldsmith and Andrew Klapper
    Tech Report, 1996.

    The 1D Illumination Problem: When Crossing Doesn’t Help
    Judy Goldsmith, Jacqueline Dodgson and Tracy Kowalski
    ACM Student Poster Competion (1994).