About

Jon Doyle is a Professor Emeritus in the Department of Computer Science at NC State University, affiliated with the College of Engineering. He holds a Ph.D. in Artificial Intelligence from the Massachusetts Institute of Technology, earned in 1980, and a Master of Science in Electrical Engineering and Computer Science from MIT, obtained in 1977. Additionally, he earned a Bachelor of Science in Mathematics from the University of Houston in 1974. His areas of expertise include Artificial Intelligence and Intelligent Agents. Dr. Doyle's academic and professional background reflects a strong foundation in computer science and AI, contributing to his recognition as a distinguished faculty member within the department.

Research topics

• Computer science
• Artificial intelligence
• Epistemology
• Psychology
• Cognitive science

Selected publications

• Ensuring Data Readiness for Quality Requirements with Help from Procedure Reuse

  Journal of Data and Information Quality · 2021-04-27 · 3 citations

  article

  Assessing and improving the quality of data are fundamental challenges in Big-Data applications. These challenges have given rise to numerous solutions targeting transformation, integration, and cleaning of data. However, while schema design, data cleaning, and data migration are nowadays reasonably well understood in isolation, not much attention has been given to the interplay between standalone tools in these areas. In this article, we focus on the problem of determining whether the available data-transforming procedures can be used together to bring about the desired quality characteristics of the data in business or analytics processes. For example, to help an organization avoid building a data-quality solution from scratch when facing a new analytics task, we ask whether the data quality can be improved by reusing the tools that are already available, and if so, which tools to apply, and in which order, all without presuming knowledge of the internals of the tools, which may be external or proprietary. Toward addressing this problem, we conduct a formal study in which individual data cleaning, data migration, or other data-transforming tools are abstracted as black-box procedures with only some of the properties exposed, such as their applicability requirements, the parts of the data that the procedure modifies, and the conditions that the data satisfy once the procedure has been applied. As a proof of concept, we provide foundational results on sequential applications of procedures abstracted in this way, to achieve prespecified data-quality objectives, for the use case of relational data and for procedures described by standard relational constraints. We show that, while reasoning in this framework may be computationally infeasible in general, there exist well-behaved cases in which these foundational results can be applied in practice for achieving desired data-quality results on Big Data.

  PublisherDOI

• Towards Greater Expressiveness, Flexibility, and Uniformity in Access Control

  2018-06-07 · 1 citations

  article

  Attribute-based access control (ABAC) is a general access control model that subsumes numerous earlier access control models. Its increasing popularity stems from the intuitive generic structure of granting permissions based on application and domain attributes of users, subjects, objects, and other entities in the system. Multiple formal and informal languages have been developed to express policies in terms of such attributes. The utility of ABAC policy languages is potentially undermined without a properly formalized underlying model. The high-level structure in a majority of ABAC models consists of sets of tokens and sets of sets, expressions that demand that the reader unpack multiple levels of sets and tokens to determine what things mean. The resulting reduced readability potentially endangers correct expression, reduces maintainability, and impedes validation. These problems could be magnified in models that employ nonuniform representations of actions and their governing policies. We propose to avoid these magnified problems by recasting the high-level structure of ABAC models in a logical formalism that treats all actions (by users and others) uniformly and that keeps existing policy languages in place by interpreting their attributes in terms of the restructured model. In comparison to existing ABAC models, use of a logical language for model formalization, including hierarchies of types of entities and attributes, promises improved expressiveness in specifying the relationships between and requirements on application and domain attributes. A logical modeling language also potentially improves flexibility in representing relationships as attributes to support some widely used policy languages. Consistency and intelligibility are improved by using uniform means for representing different types of controlled actions---such as regular access control actions, administrative actions, and user logins---and their governing policies. Logical languages also provide a well-defined denotational semantics supported by numerous formal inference and verification tools.

  PublisherDOI

• A society of mind : multiple perspectives, reasoned assumptions, and virtual copies

  Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-06-30 · 19 citations

  articleOpen access1st authorCorresponding

  Computer Science Department

  PublisherOA PDFDOI

• Some theories of reasoned assumptions : an essay in rational psychology

  Figshare · 2018-06-30 · 55 citations

  articleOpen access1st authorCorresponding

  Computer Science Department

  PublisherOA PDFDOI

• On rationality and learning

  Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) · 2018-06-30 · 7 citations

  articleOpen access1st authorCorresponding

  Computer Science Department

  PublisherOA PDFDOI

• The Data Readiness Problem for Relational Databases.

  AMW · 2018-01-01

  article
  Publisher

• What is rational psychology? : toward a modern mental philosophy

  Figshare · 2018-06-30 · 2 citations

  bookOpen access1st authorCorresponding

  Computer Science Department

  OA PDFDOI

• The ins and outs of reason maintenance

  Figshare · 2018-06-30 · 53 citations

  articleOpen access1st authorCorresponding

  Computer Science Department

  OA PDFDOI

• On universal theories of defaults

  Figshare · 2018-06-30 · 5 citations

  articleOpen access1st authorCorresponding

  Computer Science Department

  OA PDFDOI

• Expert systems without computers or theory and trust in artificial intelligence

  Figshare · 2018-06-30

  bookOpen access1st authorCorresponding

  Computer Science Department

  OA PDFDOI

Frequent coauthors

• Luc De Raedt

  KU Leuven

  162 shared

• Erik Sandewall

  116 shared

• Diana Gordon

  University of North Carolina at Charlotte

  113 shared

• Rohit Parikh

  University of North Carolina at Charlotte

  113 shared

• Zbigniew Michalewicz

  113 shared

• Lin Padgham

  RMIT University

  113 shared

• Gregory Piatetsky-Shapiro

  TE Laboratories (Ireland)

  113 shared

• Andrzej Skowron

  113 shared

Education

• Ph.D./A Model for Deliberation, Action, and Introspection, Electrical Engineering and Computer Science

  Massachusetts Institute of Technology

  1980

• S.M./Truth Maintenance Systems for Problem Solving, Electrical Engineering and Computer Science

  Massachusetts Institute of Technology

  1977

• B.S./Computational Investigations of Non-Repetitive Sequences, Mathematics

  University of Houston

  1974