Studies in Formal Logics, Uncertainty, and the Foundations of Artificial Intelligence
I have a long-standing interest in the study of intelligence and the development of mathematical models of natural human reasoning. This has led to a theory of ``qualified syllogisms'', which can be applied to some well-known problems in the field of nonmonotonic reasoning. That work includes a new kind of logical formalism, dubbed Dynamic Reasoning Systems, which explicitly portray reasoning as an activity that takes place in time. Another work has built on these ideas to create a Layman's Probability Theory for reasoning with linguistic likelihood (involving terms such as “likely,” “very likely,” “somewhat likely,” “unlikely,” etc.). More recently I have applied these same methodologies to develop a model for agent-oriented epistemic reasoning, i.e., deductions involving dispositions of knowledge and belief and employed my notion of dynamic reasoning to formulate a process of belief revision. Most recently I have been aiming this theory toward applications in expert systems and robotics.
Digital Libraries, Knowledge Management, and Applications for the Internet
Beginning in 1996 I undertook a project to develop a next-generation knowledge management system. This applies recent advances in artificial intelligence, 2D and 3D graphics, and Internet/intranet technology to the development of indexes for large distributed digital libraries. These indexes take the form of concept taxonomies (semantic networks, ontologies) having a much richer semantic structure than simple trees. In addition, the indexes are created by their own communities of users and thus comprise knowledge bases that grow and evolve over time. An underlying semantics and reasoning algorithms will be provided that will enable users to query the index as to the deeper relations between classification categories. Advanced graphics techniques will be employed to facilitate browsing, to help users find their way through these more complex structures without becoming lost or confused. I continue to develop the various components of this system through an ongoing series of masters degree programming projects.
Network Security, Intrusion Detection Systems
In recent years I have developed a new interest in Information Security. During May 2001 through April 2006 I was part of an eleven-investigator research project to study problems of critical infrastructure protection for the US Army. This work was done in collaboration with Sara Stoecklin, also at FSU, to develop a case-based reasoning (CBR) system for network intrusion detection. We employed two research assistants. The primary results were (1) an adaptive case-based reasoning framework employing reflective software architecture, and (2) application of this framework to build a multi-sensor intrusion detection system. The latter became the topic of one student’s doctoral dissertation.
I don't have pdf for the final versions of these papers. If you would like copies, please send me email with your postal address.
· Schwartz, D. G, On the possibility of an event, 25th International Joint Conference on Artificial Intelligence (IJCAI-16), New York, NY, July 9-16, 2016, submitted and in review.
· Schwartz, D. G., Dynamic reasoning systems, ACM Transactions on Computational Logic, Vol. 16, No. 4, (2015) Article 32, (2015) 69 pages including appendix.
· Schwartz, D. G., Qualified syllogisms with fuzzy predicates, International Journal of Intelligent Systems, 29(10) (2014) 926-945.
· Ustymenko, S., and Schwartz, D.G., Adapting software engineering design patterns for ontology construction, WSEAS Transactions on Information Science and Applications, 5(6).
· Ustymenko, S., and Schwartz, D.G., Dynamic agent-oriented reasoning about belief and trust, Multiagent and Grid Systems: An International Journal, 4, 2 (2008) 335-346.
· Long, J., and Schwartz, D.G., Case-oriented alert correlation, WSEAS Transactions on Computers, 7, 3 (2008) 98-112.
· Long, J., Schwartz, D., and Stoecklin, S., Multi-sensor network intrusion detection: a case-based approach, WSEAS Transactions on Computers, 4, 12 (2005) 1768-1776.
· Schwartz, D.G., Agent-oriented epistemic reasoning: subjective conditions of knowledge and belief, Artificial Intelligence, 148, 1-2 (2003) 177-195.
· Schwartz, D.G., Layman's probability theory: a calculus for reasoning with linguistic likelihood, Information Sciences, 126, 1-4 (2000) 71--82.
· Schwartz, D.G., Time, nonmonotonicity, qualified syllogisms, and the frame problem, Journal of Intelligent Systems, 8, 3-4 (1998) 315—355.
· Schwartz, D.G., Dynamic reasoning with qualified syllogisms, Artificial Intelligence, 93, 1-2 (1997) 103--167.
· Chung, H.-T., and Schwartz, D.G., A resolution-based system for symbolic approximate reasoning, International Journal of Approximate Reasoning, 13, 3 (1995) 201--246.
· Schwartz, D.G., Klir, G.J., Lewis, H., and Ezawa, Y., Applications of fuzzy sets and approximate reasoning, Proceedings of the IEEE, 82, 4 (1994) 482--498.
· Schwartz, D.G. and Klir, G.J., Fuzzy logic flowers in Japan, IEEE Spectrum, 29, 7 (1992) 32--35.
Complete List of Publications