Judy Goldsmith, Ph.D.


Research Areas: Computational complexity, computational learning theory, computational social choice, planning under uncertainty, preference handling in artificial intelligence, stochastic models, X Comparative decision-making studies

University of Kentucky, College of Engineering
Computer Science - CS
311 DMB
Lexington, KY 40506-0633
Phone: 859-257-4245
Fax: 859-323-1971
Email: goldsmit@cs.uky.edu

Professional Preparation

1988 PhD., Mathematics, University of Wisconsin

1985 M.A., Mathematics, University of Wisconsin

1982 A.B., Mathematics, Princeton University


2005 – Present Professor, University of Kentucky

Fall 2006 Adjunct Professor, University of Illinois at Chicago

Spring 2000 Visitor, Boston University

Fall 1999 Visiting Scholar, University of Illinois at Chicago

1998 – 2005 Associate Professor, University of Kentucky

1993 – 1998 Assistant Professor, University of Kentucky

1991 – 1993 Assistant Professor, University of Manitoba

1990 – 1991 Visiting Professorship for Women, NSF, Boston University

1988 – 1990 John Wesley Young Research Instructor, Dartmouth

Five Relevant Papers

  • “The computational complexity of dominance and consistency in CP-nets”, Judy Goldsmith,
    J´erˆome Lang, Mirozlaw Truszczy´nski, and Nic Wilson, Journal of Artificial Intelligence Re-
    search, Volume 33, pages 403–432.
  • “Preference Handling for Artificial Intelligence,” Judy Goldsmith and Ulrich Junker, AI
    Magazine, Winter, 2008.
  • G´abor Erd´elyi, Henning Fernau, Judy Goldsmith, Nicholas Mattei, Daniel Raible and J¨org
    Rothe, “The Complexity of Probabilistic Lobbying,” Proc. 1st International Conference on
    Algorithmic Decision Theory, 2009.
  • Thomas Dodson, Nicholas Mattei, and Judy Goldsmith, ” Natural Language Argumentation
    Interface for Explanation Generation in Markov Decision Processes,” Proc. EXaCT
    Workshop, IJCAI 2011; Proc. Algorithmic Decision Theory, 2011.
  • Judy Goldsmith and Nicholas Mattei, “Science Fiction as an Introduction to AI Research”,
    Proc. AAAI 2011, Educational Advances in AI Track, 2011.

Five Other Papers

  • “Topological Value Iteration Algorithms,” Peng Dai, Mausam, Dan Weld, and Judy Goldsmith,
    Journal of Artificial Intelligence Research, 2011.
  • “Ranking Policies in Discrete Markov Decision Processes,” Peng Dai and Judy Goldsmith,
    Annals of Mathematics and Artificial Intelligence, volume 59, Issue 1 (2010), Page 107.
  • “Planning for success: The interdisciplinary approach to building Bayesian models,” Alex
    Dekhtyar, Judy Goldsmith, Beth Goldstein, Krol Kevin Mathias, Cynthia Isenhour, Interna-
    tional Journal of Approximate Reasoning, Volume 50, Issue 3, March 2009, Pages 416–428,
    Special Section on Bayesian Modelling.
  • “Nonapproximability results for Markov decision processes,” C. Lusena, J. Goldsmith, and
    M. Mundhenk, Journal of AI Research 14: 83–103, 2001.
  • “The Computational Complexity of Probabilistic Plan Existence and Evaluation,”M. Littman,
    J. Goldsmith, and M. Mundhenk, The Journal of AI Research, volume 9, pages 1–36, 1998.

Synergistic Activities

Currently advising research projects by 4 undergraduates and and 5 PhD students, including
research on helping rheumatoid arthritis patients reason about the risks and benefits
of medication; building better academic advising systems, and (apropos of this proposal)
computational social choice. Have worked with anthropologists and psychologists on research
projects, currently working with faculty in Education and Medicine. Organizer of the
Comparative Decision Making Studies (CDMS) group at the University of Kentucky, and
currently teaching Introduction to CDMS. Affiliate and on board of directors of the Cognitive
Sciences Program at the University of Kentucky, and most recently taught the intro
survey course on cognitive sciences in Spring ’09; taught “Computational Decision Making”
in Spring ’10, and “Special Topics: Trading Agents Competition” in Fall ’10. Will be the
head of the new graduate certificate program in CDMS, involving faculty from at least 10
departments at the University of Kentucky.


Persons with whom the PI has collaborated in the past 48 months:

R. Crawford, Proctor & Gamble; A. Dekhtyar, Cal State San Louis Obispo; G. Erd´elyi,
Universit¨at D¨usseldorf; H. Fernau, Universit¨at Trier; R. Finkel, University of Kentucky;
B. Goldstein, University of Kentucky; J. Guerin, University of Kentucky; M. Hagen, Universit
¨at Jena; U. Junker, ILOG; A. Klapper, University of Kentucky; J. Lang, IRIT; K. Laskey,
George Mason University; K.K. Mathias, Humana; N. Mattei, University of Kentucky;
J. Mazur, University of Kentucky; Mausam, University of Washington; D. Raible-Binkele,
Universit¨at Trier; J. Rothe, Universit¨at D¨usseldorf; R. Sloan, UIC; M. Truszczy´nski, University
of Kentucky; D. Weld, University of Washington; N. Wilson, Cork Co. Constraint
Center; L. Yi, Tom Sawyer Software.

Advisees in last 5 years:

PhD students: Krol Kevin Mathias (’09), Liangrong Yi (’10), Joshua Guerin (’12?), Nicholas
Scott Mattei (’12?), Radu Paul Mihail (’13?), Ju Shen (’13?), Matthew Spradling (’14?)
University of Kentucky

MS students: Daniel Michler (’12?) Peng Dai (’07), University of Kentucky

Total number of advisees: 2 postdocs, 7 PhD students, 12 MS students, 17 undergrads, 2
high school students

PI’s advisors:

D. Joseph, University of Wisconsin-Madison; M. Groszek, Dartmouth College; S. Homer,
Boston University.