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‫תקציר קורות חיים‬
‫פרופ' רחל בן‪-‬אליהו – זהרי נולדה וגדלה בירושלים‪ .‬למדה בבית ספר יסודי דתי מימון ואח"כ בבית‬
‫ספר בויאר‪ .‬שרתה בצבא שירות מלא בתפקיד מאבחנת פסיכוטכנית‪ .‬סיימה תואר ראשון במתמטיקה‬
‫ומדעי המחשב בהצטיינות מטעם האוניברסיטה העברית‪ ,‬ולאחר מכן עבדה במשך שנתיים כמהנדסת‬
‫תוכנה בחברת טלרד‪ .‬את עבודת המחקר שלה לתואר שני במדעי המחשב עשתה בהנחיית פרופ'‬
‫מנחם מגידור בתחום של לוגיקה טמפורלית‪ ,‬ואילו את תואר הדוקטורט שלה במדעי המחשב קיבלה‬
‫מאוניברסיטת קליפורניה‪ ,‬לוס אנג'לס )‪ ,(UCLA‬שם עסקה במחקר בתחום הבינה המלאכותית‬
‫בהנחייתם של פרופ' יהודה פרל ופרופ' רינה דכטר‪ .‬לאחר הדוקטורט חזרה לארץ ועבדה בפקולטה‬
‫למדעי המחשב בטכניון כחוקרת במשרת פוסט‪-‬דוקטורט במשך שנתיים‪ ,‬ואחר כך הייתה חברת סגל‬
‫בתקן במחלקה למדעי המחשב ובמחלקה להנדסת מערכות תקשורת באוניברסיטת בן‪-‬גוריון במשך‬
‫כ‪ 8-‬שנים‪ .‬פרופ' בן‪-‬אליהו –זהרי משמשת כראש המחלקה להנדסת תוכנה במכללה האקדמית‬
‫להנדסה ירושלים מאז שנת ‪ .3002‬במחלקה ‪ 020‬סטודנטים‪ .‬במהלך כהונתה בתפקיד זה‪ ,‬המחלקה‬
‫קיבלה הסמכה קבועה להעניק תואר ‪ B.Sc.‬בהנדסת תוכנה ואישור להגיש תכנית לתואר שני בהנדסת‬
‫תוכנה‪ .‬במחקרה פרופ' בן‪-‬אליהו עוסקת בייצוג ידע וכריית נתונים ומידע ופרסמה מאמרים רבים‬
‫בתחום זה בעיתונים וכנסים יוקרתיים‪ .‬קורות חיים מפורטים מצ"ב בהמשך באנגלית‪.‬‬
‫‪CURRICULUM VITAE‬‬
‫‪Name: Ben-Eliyahu- Zohary Rachel‬‬
‫‪Citizenship: Israeli‬‬
‫‪Address: 11 Brachyahoo St. Beit Hakerem 96225‬‬
‫‪Jerusalem‬‬
‫‪Tel: 972-2- 6427438, Mobile: 972-50-8958830‬‬
‫‪Military Servise: 1977-1979, Psychotechnical Diagnostician‬‬
‫‪Academic Education‬‬
‫‪Hebrew University, Mathematics and Computer Science, B.Sc.‬‬
‫‪Hebrew University, Computer Science, M.Sc.‬‬
‫‪UCLA, Computer Science, Ph.D.‬‬
‫‪1979-1983‬‬
‫‪1985-1987‬‬
‫‪1987-1993‬‬
‫‪Academic Employment‬‬
‫‪2007-present, Ben-Gurion university department of communication systems‬‬
‫‪engineering, Senior Lecturer‬‬
‫‪2006-present, JCE – Jerusalem College of Engineering, Associate Professor, Head of‬‬
‫‪Software Engineering Department.‬‬
‫‪August 2004- August 2005, Harvard Division of Engineering and Applied Sciences,‬‬
‫‪Visiting Scholar, Research and Teaching‬‬
‫)‪2003-2006 (on sabbatical 2004-05‬‬
JCE – Jerusalem College of Engineering, Senior Lecturer, Head of Software
Engineering Department
2000-present (on maternity leave 2002, on leave 2003-2006)
Ben-Gurion university department of communication systems engineering, Senior
Lecturer, Head of study programs committee and head of teaching committee.
1995-1998
Ben-Gurion university department of computer science, Lecturer, Head
of study programs committee.
1993-1995
Technion – faculty of computer science, Post-doctoral researcher.
1990 – 1993 UCLA – department of
laboratory, Research Assitant.
computer science – cognitive systems
1988 -1990 UCLA – department of mathematics and department of computer
science, Teaching Assistant.
1988-1990
IBM Los-Angeles Scientific
Programmer.
Center, Research Assistant and
Other employments
 October 1983 - August 1985, Senior Programmer/Analyst,
Telrad Telecommunication and Electronics Industries Ltd, Israel.
Involved in development of public digital switchboard and data
communication systems.
 October 1987 - August 1993, System Manager, Computing resources
group, UCLA medical center, Managing two MicroVAXs with operating
system VMS.
 December 2000 –November 2002, Chief Scientist, Infocyclone LTD, Tel-Aviv,
Israel (a consulting position, patent pending).
Academic Activities

Referee in several AI, logic programming, and theoretical computer science
conferences, including AAAI-2002, BISFAI-2001, BISFAI-05, IJCAI-91,
IJCAI-93, IJCAI-95, IJCAI-99, IJCAI-2001, IJCAI-2003, IJCAI-2005, IJCAI2011, AAAI-92, AAAI-94, AAAI-99, AAAI-10, JICSLP-92, ICLP-93, and
FOCS-2001. (BISFAI: "Bar-Ilan International Symposium on Foundation of
Artificial Intelligence". AAAI: "National conference on Artificial Intelligence".
IJCAI: "International Joint conference on Artificial Intelligence". FOCS:
“Foundations of Computer Science”.

Referee for several journals, including "Journal of AI research","Artificial Intelligence",
"Information and Computation", "Annals of Mathematics and AI'', "Journal of
Automated Reasoning", "Journal of Applied Intelligence", “Artificial Intelligence
Communications”, "journal of logic programming'', "IEEE transactions on Knowledge
and Data Engineering”, “Computational Intelligence”, and TPLP (Theory and Practice of
Logic Programming).

Member of the review board for the journal "Applied Intelligence", 1995.

Co-chair of an international workshop in IJCAI-95. Montreal, Canada, August
1995. The workshop was on "Applications and implementations of nonmonotonic
systems".

On the program committee of the 1996 international symposium on Artificial
Intelligence and Mathematics, Fort Lauderdale, Florida, January 1996.

On the program committee of AAAI-10, AAAI-11, AAAI-96, AAAI-98, AAAI99, AAAI-02, IJCAI-97, and IJCAI-2007.

On the program committee of JELIA-02: the Joint European conference on Logic
and Artificial Intelligence.

On the editorial board of the journal of Artificial Intelligence Research, 19982001.

On the program committee of BISFAI-05: Biennial Israeli Symposium on the
Foundations of AI, 2005.

On the board of the Israeli Association for Artificial Intelligence (IAAI), 20052006.

On the program committee of ECAI-06: The 17th European Conference on
Artificial Intelligence, 2006.
Contribution to the development of the academic corriculum:
 Head of the study programs committee in the department of
CommunicationSystems Engineering (CSE), Ben-Gurion University (BGU),
for two years. Responsible for the following activities, among others:
1.
Developing the M.Sc. program for the department.
2.
Developing an M.Sc. program in Computer Science for graduates
of the CSE department.
3.
Responsible for a major review and and revision in the B.Sc.
program.
 Head of the teaching committee in the CSE department, BGU, for two years.
 Head of the department of Software Engineering, Jerusalem College of
Engineering. Managing the department and responsible for upgrading the
degree granted from B.Tech to B.Sc.
Courses taught:
Courses taught in the Department of Electrical Engineering, Ben-Gurion University:
 Programming with Pascal ("Tichnoot 1") Courses taught in the Department of
Mathematics and Computer Science, Ben Gurion University:
 Principles of programming languages
 Compiler design
 Artificial Intelligence
 Seminars on specific topics in Artificial Intelligence, like nonmonotonic
reasoning, model-based diagnosis, and logic programming.
Courses taught in the Department of Communication Systems Engineering,
Ben-Gurion University:
 Algorithms
 Artificial Intelligence
 Foundations of Computer Science
 Files and databases
Courses taught in the Department of Software Engineering, JCE:
 Compiler Design
 Artificial Intelligence
Courses taught in the Department of Industrial and Management Engineering, JCE
(2005-2006):
 Artificial Intelligence
 Algorithms for Information Systems
 Data Structures
Courses taught in the Division of Engineering and Applied Sciences, Harvard
University:
 Modal logic of knowledge and its application in multi-agent systems
(four guest lectures in the course on multi-agent systems).
Fellowships




Hebrew University Fellowship, 1980-1983.
UCLA Fellowship, 1988.
IBM graduate Fellowship, 1992-1993.
Lady Davis post-doctoral Fellowship, 1993-1995.
Grants and Awards
Honors


B.Sc with distinction, Hebrew University, Jerusalem, Israel.
M.Sc with distinction, Hebrew University, Jerusalem, Israel
Grants
Source
1. consortium for network
management systems
2. consortium for network
management systems
3. Ministry of Science
("Tashtit'')
Amount
$90,000
Period
1996-1997
Co-investigators
Ran Giladi, Dan
Reuven Cohen
Ran Giladi
$25,000
1997-1998
$300,000
1996-1999
4. Ben-Gurion UniversitySeed grant
$10,000
2002
5. Consortium IMG$ - the 4th
Generation
of
Imaging
Machines
6. Consortium IMG$ - the 5th
Generation
of
Imaging
Machines
620,000
INS
2007-2009
Eyal Shimony, Ehud Gudes
338,000
INS
2009-2010
Ehud Gudes
Eyal
Shimony,
Meisels, Ehud Gudes
List of Publications
 Dissertations
1. Ph.D. in Computer Science, University of California, Computer Science
Department, Los Angeles, California (UCLA), June 1993 Topic of Dissertation:
Computational aspects of nonmonotonic Reasoning.
Advisors: Professor Judea Pearl (UCLA) and Professor Rina Dechter (UCI). Parts
of the dissertation were published in journal papers no. 1 and no. 5 below.
2. M.Sc. in Computer Science, Hebrew University, Jerusalem, Israel, July 1987.
Advisor: Professor Menachem Magidor. Topic of Dissertation: "Proving
correctness for the general execution" Part of the dissertation was published in
journal paper no. 2 below.
 Refereed articles in scientific journals
1. Rachel Ben-Eliyahu and Rina Dechter, "Propositional semantics for disjunctive
logic programs", Annals of Mathematics and Artificial Intelligence, volume 12,
pp. 53-87,1994.
2. Rachel Ben-Eliyahu and Menachem Magidor, "A temporal logic for proving
properties of topologically general executions", Information and Computation,
volume 124(2), pp. 127-144, 1996.
Geiger,
Amnon
3. Rachel Ben-Eliyahu, "A Hierarchy of tractable subsets for computing stable
models", Journal of Artificial Intelligence Research, volume 5, pp. 27-52, 1996.
4. Rachel Ben-Eliyahu and Rina Dechter, "On computing minimal models",
Annals of Mathematics and Artificial Intelligence, volume 18, pp. 3-27, 1996.
5. Rachel Ben-Eliyahu and Rina Dechter, "Default reasoning using classical logic",
Artificial Intelligence, volume 84 (1-2), pp. 113-150, 1996.
6. Krzysztof Apt and Rachel Ben-Eliyahu, "Meta variables in logic programming,
or in praise of ambivalent syntax", Fundamenta Informaticae, volume 28, pp.
23-36, 1996.
7. Rachel Ben-Eliyahu and Luigi Palopoli,"Reasoning with minimal models:
efficient algorithms and applications'', Artificial Intelligence, volume 96 (2),
pp. 421-449, 1997.
8. Rachel Ben-Eliyahu, Nissim Francez, and Michael Kaminski,"Similarity
preservation in default logic", Annals of mathematics and Artificial Intelligence,
volume 25 (1-2), pp. 137-160, 1999.
9. Rachel Ben-Eliyahu, Luigi Palopoli, and Victoria Zemlyanker, “More on
tractable disjunctive Datalog”, Journal of Logic Programming, volume 46(1-2),
pp. 61-101, 2000.
10. Shai Ben-David and Rachel Ben-Eliyahu, "A modal logic for subjective default
reasoning'', Artificial Intelligence, volume 116(1-2), pp. 217-236, 2000.
11. Rachel Ben-Eliyahu, “Yet some more complexity results for default logic”,
Artificial Intelligence, volume 139(1), pp. 1-20, 2002.
12. F. Angiulli, Rachel Ben-Eliyahu, G. B. Ianni, and L. Palopoli, "Computational
properties of metaquerying problems", ACM Transactions on Computational
Logic (TOCL), volume 4(2), pp. 149-180, 2003.
13. Rachel Ben-Eliyahu, Ehud Gudes and G. B. Ianni, “Metaqueries: Semantics,
Complexity, and Efficient Algorithms", Artificial Intelligence, volume 149(1),
pp. 61-87, 2003.
14. Rachel Ben-Eliyahu, C. Domshlak, D. Gershkovich, E. Gudes,N. Liusternik, A.
Meisels, T. Rosen and S.E. Shimony, “FlexiMine - A flexible platform for KDD
research and application development", Annals of Mathematics and Artificial
Intelligence volume 39(1-2) pp. 175-204, 2003.
15. Rachel Ben-Eliyahu, "A demand-driven algorithm for generating minimal
models", Artificial Intelligence, volume 169 pages 1-22, 2005.
16. Chen Avin and Rachel Ben-Eliyahu, “An upper bound on computing all Xminimal models”, Artificial Intelligence Communications 20 (2), pages 87-92,
2007.
17. F. Angiulli, R. Ben-Eliyahu – Zohary, and L. Palopoli, "Outlier detection
using default reasoning" . Artificial Intelligence, volume 172 (16-17), pages
1837-1872, 2008.
18. F. Angiulli, R. Ben-Eliyahu – Zohary, and L. Palopoli, "Outlier detection in
simple default theories" . Artificial Intelligence, volume 174 (15), pages 12471253 , 2010.
19. S. Albagli, R. Ben-Eliyahu – Zohary, and E. Shimony, "Markov Network
based Ontology Matching", special issue of the Journal of Computer and
System Sciences devoted to Knowledge Representation and Reasoning, volume
78 Issue 1, January 2012.
Chapters in collective volumes - Refereed conference proceedings
1. Rachel Ben-Eliyahu and Rina Dechter, "Default logic, propositional logic and
constraints",In AAAI-91: Proceedings of the 9th national conference on artificial
intelligence, pages 379-385, July 1991.
2. Rachel Ben-Eliyahu and Rina Dechter,"Inference in inheritance networks using
propositional logic and constraints networks techniques", In AI-92: Proceedings of
the 9th Canadian conference on AI, pages 183-189, Vancouver, British Columbia,
Canada, May 1992.
3. Rachel Ben-Eliyahu and Rina Dechter,"Propositional semantics for disjunctive
logic programs", In JICSLP-92: Proceedings of the 1992 Joint International
Conference and Symposium on Logic Programming, pages 813-827, Washington
DC, November 1992.
4. Rachel Ben-Eliyahu and Rina Dechter,"On computing minimal models", In
AAAI-93: Proceedings of the 11th national conference on artificial intelligence,
pages 2-8, July 1993.
5. Rachel Ben-Eliyahu,"Back to the future : Program completion, revisited", In
IAICVINN-93: proceedings of the 10th Israeli Symposium on Artificial
intelligence, computer vision, and Neural networks, pages 61-70, December 1993.
6. Rachel Ben-Eliyahu and Luigi Palopoli,"Reasoning with minimal models:
Efficient algorithms and applications",In KR-94: proceedings of the 4th
International conference on principles of knowledge representation and reasoning,
pages 39-50, May 1994.
7. Shai Ben-David and Rachel Ben-Eliyahu,"A modal logic for subjective default
reasoning", In LICS-94: proceedings of the 9th annual IEEE symposium on logic
in computer science, pages 477-486, July 1994.
8. Rachel Ben-Eliyahu, Luigi Palopoli, and Victoria Zemlyanker,"The expressive
power of tractable disjunction'', Proc. of the European Conference on Artificial
Intelligence, Budapest, pages 345-349, 1996.
9. Rachel Ben-Eliyahu and Ehud Gudes, "Towards efficient metaquerying", in
IJCAI-99: Proceedings of the 16th international joint conference on artificial
intelligence, pages 800-805, Stockholm, Sweden, 1999.
10. F. Angiulli, Rachel Ben-Eliyahu, G. B. Ianni, and L. Palopoli,"Computational
properties of metaquerying problems", in PODS2000: Proceedings of the 19th
ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems.
pages 237-244, San-Diego, California, USA, 2000.
11. Rachel Ben-Eliyahu, "A demand-driven algorithm for generating minimal
models", in AAAI-2000: the 17th National Conference on Artificial Intelligence,
pages 267-272, Austin, Texas, 2000.
12. Chen Avin and Rachel Ben-Eliyahu, “Algorithms for computing x-minimal
models”, in proceedings of LPNMR-2001: the 6th International Conference on
Logic Programming and Nonmonotonic Reasoning. LNCS 2173, pages 322-335,
2001
13. Fabrizio Angiulli, Rachel Ben-Eliyahu and Luigi Palopoli,“Outlier Detection
using Default Logic”, in IJCAI-03: Proceedings of the 18th international joint
conference on artificial intelligence, pages 833-838, 2003.
14. Fabrizio Angiulli, Rachel Ben-Eliyahu and Luigi Palopoli, “Outlier Detection
using Disjunctive Logic Programming”, in ECAI-04: Proceedings of the 16th
European conference on Artificial Intelligence, pages 416-419, 2004.
15. S. Albagli, R. Ben-Eliyahu – Zohary, and E. Shimony, "Markov Network
based Ontology Matching", in IJCAI-09: Proceedings of the 21st international
joint conference on artificial intelligence, pages 1884-1889, 2009.
Technical Reports
1. Rachel Ben-Eliyaho "NP-Complete problems in optimal Horn clauses
satisfiability", Technical Report R-158,Cognitive systems lab, UCLA, 1990
2. Rachel Ben-Eliyahu and Rina Dechter, "Translating a cyclic default theory
into an acyclic default theory,Technical report R-169, Cognitive systems lab,
UCLA, 1991".
3. Rachel Ben-Eliyahu and Luigi Palopoli,"The expressive power of stratified
Datalog over ordered databases",Technical report R-225, Cognitive systems lab,
UCLA, 1994.
4. Rachel Ben-Eliyahu,"Proving correctness for the general execution",Master
thesis, the Hebrew University, Jerusalem, Israel, 1987
Lectures and Presentations at Meetings and Invited Seminars
 Presentations at informal international seminars and workshops
1. Rachel Ben-Eliyahu and Rina Dechter,"On computing minimal models",
Presented at the AAAI spring symposium on AI and NP-hard problems,
Stanford university, California, March 1993.
2. Rachel Ben-Eliyahu and Rina Dechter, "Default logic, propositional logic, and
constraints", Presented at the AAAI spring symposium on Constraint Based
Reasoning, March 1991.
3.
Rachel Ben-Eliyahu and Rina Dechter,"Propositional semantics for default
logic", Presented at the 4th international workshop on nonmonotonic
reasoning, May 1992, Plymouth, Vermont.
4.
Rachel Ben-Eliyahu and Rina Dechter,"Propositional semantics for
disjunctive logic programs".Presented at the disjunctive logic programming
workshop, international logic programming symposium, San-Diego, 1991.
5.
Rachel Ben-Eliyahu, "Back to the future : Program completion, revisited". A
poster in the international logic programming symposium, Vancouver,
Canada, October 1993.
6.
Rachel Ben-Eliyahu and Luigi Palopoli, "Model selection in disjunctive logic
programming: algorithms and expressibility". Presented at the 2nd workshop
on structural complexity and recursion theoretic methods in logic
programming and in the workshop on logic programming with incomplete
information, international logic programming symposium, Vancouver,
Canada, October 1993.
7. Rachel Ben-Eliyahu, Nissim Francez and Michael Kaminski,"Similarity
preservation in default logic", presented at the specialized workshop on
Formal Aspects and Applications of Nonmonotonic Reasonin in conjunction
with NMR-98.
8. Rachel Ben-Eliyahu,"Head cycle free logic programs", Lecture at the Dagstuhl
seminar on disjunctive logic programming and databases: Non-Monotonic
Aspects, Germany, July 1996.
9.
Rachel Ben-Eliyahu, "New algorithms for computing minimal models",
Lecture at the Dagstuhl seminar on Nonmonotonic Reasoning, Answer Set
Programming and Constraints, Germany, September 2002. R. Ben-EliyahuZohary, R. Giladi, P. Hendirix and S. Shieber, “Clustering Ad-Hoc Networks
using Local Search” – presented at BISFAI 2008 – Bar-Ilan symposium on the
Foundations of AI.
10. R. Ben-Eliyahu-Zohary, R. Giladi, P. Hendirix and S. Shieber, “Clustering
Ad-Hoc Networks using Local Search” – presented at BISFAI 2008 – Bar-Ilan
symposium on the Foundations of AI.
11. Rachel Ben-Eliyahu-Zohary, “Quantified Logic Programs, Revisited” ,
presented at the Workshop on Answer Set Programming and Other Computing
Paradigms (ASPOCP) 2008
12. Sivan Albagli, Rachel Ben-Eliyahu and Eyal Shimony, “Markov Networks
based Ontology Matching, presented at NGITS 2009 - The 7th conference on
Next Generation Information Technologies and Systems, 2009.
13. Fabrizio Angiulli, Rachel Ben-Eliyahu-Zohary and Luigi Palopoli. Tractable
Strong Outlier Identification. Prsented at the The 9th International Workshop
on Nonmonotonic Reasoning, Action and Change (NRAC-2011), 2011.
14. Fabrizio Angiulli, Rachel Ben-Eliyahu-Zohary and Luigi Palopoli. Tractable
Strong Outlier Identification. Prsented at the The 9th International Workshop
on Nonmonotonic Reasoning, Action and Change (NRAC-2011), 2011.
15. Fabrizio Angiulli, Rachel Ben-Eliyahu-Zohary and Luigi Palopoli. Tractable
Strong Outlier Identification. The 11th Bar-Ilan Symposium on the
Foundations of Artificial Intelligence (BISFAI), 2011.
16. Rachel Ben-Eliyahu-Zohary, Elena Curkin, Tal Grinshpoun and Ehud Gudes,
Ontology matching using qualitative logic programs, a poster in The 11th
Bar-Ilan Symposium on the Foundations of Artificial Intelligence
(BISFAI), 2011.
 Seminar presentations at universities and institutions
1.
2.
3.
4.
1992, School of Mathematics and Computer science, Tel-Aviv University.
1992, Department of Mathematics, Haifa university, Israel.
1992, IBM Research Center, Haifa, Israel.
1992, Faculty of Mathematics and Computer Science, Weizmann Institute of
Science, Rehovot, Israel.
5. 1993, Department of Computer Science, University of California, Riverside.
6. 1994, Computer Science Department, Hebrew University of Jerusalem.
7. 1995, Department of Engineering and Information Systems,Universita della
Calabria, Italy.
8. 1998, Institute of Information Systems, Vienna University of Technology,
Vienna, Austria.
9.
2000, Universita della Calabria, Italy, an invited course on model-based
diagnosis.
10. 2002, School of Management, the Hebrew University, Israel.
11. 2003, Faculty of Mathematics and Computer Science, Weizmann
Institute of Science, Rehovot, Israel.
12. 2004, AI Research Group, Division of Engineering an Applied Sciences,
Harvard, Cambridge, MA, U.S.A
13. 2005, Division of Engineering and Applied Sciences Harvard, Cambridge,
MA, U.S.A, invited lectures on modal logic of knowledge.
14. 2006, Universita della Calabria, Italy, an invited course on modal logic of
knowledge.
15. 2008, Universita della Calabria, Italy, an invited course on modal logic of
knowledge.
Patents
Levy, E., Kfir, Z., Kaplan, Y., Ben-Eliyahu, R., Turkel, I., Moskovich, R., Menachi, E.,
Giladi, R., Gang, S., Shurman, M., “Dynamic Information Retrieval System”, US Patent No.
60/359,247, February 2002.
SYNOPSIS OF RESEARCH
My research aims to contribute to the expansion of the application of mathematical logic in computer
science, and to the usage of tools developed in the Artificial Intelligence community for solving
problems in computer networking. During my M.Sc. degree research, I have been working on
application of Propositional Temporal Logic to program verification. Since I have started my PhD
research, I am doing research in the area of Knowledge Representation (KR), Logic Programming, and
Databases. My general theme is to make commonsense reasoning a reality, that is, to bring it closer to
implementation, both conceptually and computationally. My contribution to the area of KR can be
divided into four (not necessarily disjoint) categories: semantic issues, using classical logic for default
reasoning, Head–Cycle–Free logic programs, and knowledge discovery in databases. I will first
describe my M.Sc. research and then elaborate on my work in knowledge representation. Finally I will
briefly describe my work in communication networks.
Application of Temporal Logic to program verification
Together with my M.Sc. advisor, Menachem Magidor, I have developed a generalization of
the Temporal Propositional Logic of linear time which is useful for stating and proving
properties of the generic execution sequence of a parallel program or a non-deterministic
program. The formulation that we have used allows stating properties of most of the possible
executions, where “most of” is defined precisely using mathematical set-theoretic
terminology. I have presented a formal system of axioms and showed that it is decidable,
sound, and complete for models of arbitrary size, but has the finite model property; namely,
every sentence that has a model also has a finite model. The results of this work are presented
in the journal publication [2].
Semantics issues in default logic and logic programming
One of the benefits of using classical logic for KR is that we can achieve clear semantics of
the systems developed. I have worked on three semantics issues in default logic and logic
programming.
In the work presented in journal publication [10], I have developed (with Shai Ben-David) the
logic DML: Default Modal Logic. In DML we use the set-theoretic notion of “filters” to
establish a generalization of the probabilistic interpretations of default reasoning. I have
shown that any modal semantics that is sound for some basic axioms of default reasoning is a
special case of our semantics.
Meta-variables, that is, variables that can be instantiated by predicate names, are useful in
Prolog but their usage lacks clear semantics. My work published in journal publication [6]
(with K. Apt) is on extending the usual theory of SLD-resolution to give semantics to logic
programs with meta-variables.
In journal publication [8] (together with N. Francez and M. Kaminski) I have addressed the
problem of similarity preservation in Default Logic. The problem is that often, elements that
are similar given the axioms only, become distinguishable in extensions. I have explained
why this is sometimes undesirable and have presented two equivalent approaches to avoid this
situation.
Using classical logic for default reasoning
A major component in commonsense reasoning is the management of default sentences like
“birds fly” and “the train will reach its destination”. Default statements are taken to be true
under all practical instances, only to be defeated by conflicting evidence and other such
defaults. The problem of learning and reasoning with defaults has been on the Artificial
Intelligence agenda for many years, and one of my goals is to help make default reasoning
practical. In the previous section I have mentioned two research projects (journal papers [8]
and [10]), which helped solve semantics difficulties in default reasoning. Another problem is
the high complexity of reasoning with defaults.
During my Ph.D. research, under the supervision of Rina Dechter and Judea Pearl, I have
explored methods by which nonmonotonic reasoning can be understood and expressed in
terms of classical logic. The goal was to attribute clear semantics to default logics and to
exploit the algorithms already used in classical logic for nonmonotonic reasoning.
I have shown that default theories can be characterized by classical propositional theories.
This work has paved the way for application of decades of continuing research on efficient
algorithms for the satisfiability problem to default reasoning. I have demonstrated this idea by
using the taxonomy of tractable CSP (constraint satisfaction problems) to identify new
tractable subsets for default logic. Recently, there was a renewed interest in this work of mine
as it was realized by many researchers that default reasoning systems that are based on the
idea of translation to propositional logic can be very efficient.
My work on default logic is presented in detail in journal publication [5]. A special case is the
class of inheritance networks, and the application of my approach to inheritance networks is
explained in conference paper [2].
I was also concerned with applying the “default reasoning using classical logic” idea in the
area of extended, disjunctive, logic programs (EDLPs) (journal publication [1]). This is the
most general form of propositional logic programs, where disjunction is allowed in heads of
rules and where two types of negation are used: the usual “negation as failure” and classical
negation. I have identified a subclass EDLPs, which I have
called Head-Cycle-Free (HCF) EDLPs, for which the translation is tractable. Consequently, I
have shown that coherence and membership for the class HCF is NP-complete and entailment
is co-NP-complete. It turns out that my translation of HCF programs is a generalization of
Clark’s predicate completion, a known semantics for logic programs that is based on
translation to classical logic. This work is reported in journal publication [5].
The class HCF was later found to be a very interesting one since on the one hand it is much
more manageable than the general disjunctive logic programs complexity-wise, and on the
other hand it is quite expressive. This issue is elaborated in detail in the next section.
Head – Cycle –Free (HCF) theories and logic programming
HCF theories are a subset of all propositional theories which is by now well known in the
community of researches interested in disjunctive logic programs and disjunctive deductive
databases (Datalog). The class was first introduced in my work with R. Dechter published in
journal publication [1]. Intuitively, a theory is HCF (Head Cycle Free) if and only if there are
no two atoms in the head of the same clause that are dependent on each other.
The problems of finding a minimal model of a theory (model finding) and checking whether a
given model is minimal (model checking) are relevant to diagnosis tasks in AI and to model
computation in logic programming. These computational tasks are known to be very hard for
arbitrary propositional theories. Even for positive theories (theories in which each clause has
at least one atom in the head) these problems are NP-hard or co-NP-hard. I have discovered
(together with L. Palopoli) linear algorithms for model finding and model checking for the
class of positive HCF theories (see journal publication [7]).
The class HCF can be recognized in polynomial time and hence has a significant influence on
efficient computation of models. In the KR system dlv, developed at Vienna University of
Technology, it has been shown that by using modular evaluation techniques, that is, by using
polynomial algorithms for portions of the program that are HCF, a substantial speed up in
computation can be obtained.
Next (with L. Palopoli and my student V. Zemlyanker), I have explored the existence of
supersets of HCF disjunctive Datalog that are still tractable, and classified their expressive
power. The motivation was the observation that although HCF disjunctive Datalog programs
are tractable, they cannot express all polynomial time queries. In journal publication [9] I
have shown that the most expressive of the tractable languages that I have considered can
express, in some precise sense, all polynomial time queries. That language is the first
identified fragment of disjunctive Datalog with this property.
In the work reported at journal publication [4], I have developed (together with R. Dechter)
efficient algorithms for minimal model finding. We have presented two groups of algorithms.
Algorithms in the first group are useful when the theory is close to being a Horn theory, in
some precise sense. Algorithms in the second group are
efficient when the theory can be represented as an acyclic network of low-arity relations.
Stable model semantics is nowadays the most popular semantics for extended logic programs.
Recently, it has been used for planning in general and for planning in multi-agent systems in
particular. The computational obstacle is that while it is possible to compute a model of a
stratified logic program in linear time, the task of computing a stable model of a general, not
necessarily stratified, program is NP-hard. Hence, several researchers have suggested
heuristics for computing stable models. The problem with the algorithms suggested by other
researchers is that they are exponential also for stratified programs.
In my work presented at journal publication [3], I tried to find out whether the computational
complexity gap between stratified and general logic programs can be abridged. Indeed, I have
succeeded in presenting a hierarchy of all logic programs, where stratified programs are at the
bottom and a program will be far higher in the hierarchy as it is less and less stratified. I have
also developed an algorithm for stable model computation that will work more and more
efficiently as the program resides lower and lower in the hierarchy. For stratified programs,
my algorithm is linear. Another advantage of my algorithm is that it is modular and different
algorithms can be used for computing different portions of the program.
In journal publication [15], I have developed a demand-driven algorithm for computing
minimal models. The algorithm for generating minimal models has some common ideas with
the algorithm for generating stable models presented in journal publication [3], however, it
finds all the minimal models, not necessarily the stable ones, and it works for rules having
more than one atom in the head.
Knowledge discovery in databases
I was also involved in research in knowledge discovery in databases (KDD). KDD is also a
form of reasoning, but instead of deducing facts, we want to learn rules, or patterns. I was part
of a project developing a KDD system that is a test bed for data-mining research and a generic
discovery tool for various database domains. Several knowledge discovery techniques were
implemented in that system, including association rules, decision trees, Bayesian knowledge
bases and metaqueries. The system is described in the journal publication [14].
Within the KDD project, I was especially interested in algorithms for Metaqueries.
Metaquery, or Metapattern, is a datamining tool useful for learning rules involving more than
one relation in the database. A metaquery is a template that describes the type of pattern to be
discovered. This tool has already been successfully applied to several real-world applications.
I have contributed to the research on metaqueries in several ways: together with F. Angiulli,
G. B. Ianni, and L. Palopoli (journal publication [12]), I have analyzed computational
problems related to metaquerying and redefined some of the basic concepts that accompany
metaquery computation (concepts like confidence and
support). In journal publication [13] I have proposed, together with E. Gudes and G.B. Ianni,
some efficient algorithms for meta querying and conducted experiments that show that the
algorithms that I have developed are indeed very useful.
In conference publication [13] I have studied, together with F. Angiulli and L. Palopoli, the
problem of outlier detection using default logic.
Together with F. Angiulli and L. Palopoli, I have also worked on knowledge discovery in the
framework of default logic. Default logics are usually used to describe regular behavior and
normal properties of individuals. In conference publications [13] and 14], I have suggested to
exploit the framework of default logics for detecting outliers - individuals who behave in an
unexpected way or feature abnormal properties. The ability to locate outliers can help to
maintain knowledgebase integrity and to single out irregular individuals. In this research
project, I have defined the notion of outlier in two related formalisms for specifying defaults:
Reiter's default logic and extended disjunctive logic programs. I have also made an extensive
complexity analysis and identified tractable classes for each of the two formalisms. A journal
paper that summarizes this project is in preparation.
Application of AI tools to computer networks
In the last few years I have been involved in several projects in which tools developed
in the AI community are used in communication networks tasks. In projects supported
by grants 1,2, and 4 (see “grants” section), we have worked on using formal methods
for diagnosis for detecting and managing faults in computer networks. Journal
publications [7,15] report on my work on computing minimal models, one of the main
tasks in formal system diagnosis.
In a recent work with R. Giladi (BGU), P. Hendrix and S. Sheiber (Harvard), I have
shown how the local search method called “simulated annealing” can outperform a
systematic algorithm having a pre-calculated upper bound on the task of clustering
Ad-Hoc wireless networks. A paper by the name “Clustering Ad-Hoc Wireless
Networks by Simulated Annealing” is in preparation for publication in the journal
“IEEE Communication letters”. Another direction that I would like to investigate is
using the knowledge discovery and datamining tools that I have developed for
improving network performance.

Articles to be published – submitted
R. Ben-Eliyahu-Zohary, R. Giladi, P. Hendirix and S. Shieber, “Clustering AdHoc Networks using Local Search”

In Preparation
1. F. Angiulli, R. Ben-Eliyahu – Zohary, and L. Palopoli, "Tractable Outlier
detection using default reasoning" .
2. Rachel Ben-Eliyahu-Zohary , Quantified Logic Programmin.