PAN: A portable,parallel Prolog: Its design,realisation and performance

PAN is a general purpose, portable environment for executing logic programs in parallel. It combines a flexible, distributed architecture which is resilient to software and platform evolution with facilities for automatically extracting and exploiting AND and OR parallelism in ordinary Prolog programs. PAN incorporates a range of compile-time and run-time techniques to deliver the performance benefits of parallel execution while rertaining sequential execution semantics. Several examples illustrate the efficiency of the controls that facilitate the execution of logic programs in a distributed manner and identify the class of applications that benefit from distributed platforms like PAN. George Xirogiannis, Ph.D.: He received his B.S. in Mathematics from the University of Ioannina, Greece in 1993, his M.S in Artificial Intelligence from the University of Bristol in 1994 and his Ph.D. in Computer Science from Heriot-Watt University, Edinburgh in 1998. His Ph.D. thesis concerns the automated execution of Prolog on distributed heterogeneous multi-processors. His research interests have progressed from knowledge-based systems to distributed logic programming and data mining. Currently, he is working as a senior IT consultant at Pricewaterhouse Coopers. He is also a Research Associate at the National Technical University of Athens, researching in knowledge and data mining. Hamish Taylor, Ph.D.: He is a lecturer in Computer Science in the Computing and Electrical Engineering Department of Heriot-Watt University in Edinburgh. He received M.A. and MLitt degrees in philosophy from Cambridge University and an M.S. and a Ph.D. degree in computer science from Heriot-Watt University, Scotland. Since 1985 he has worked on research projects concerned with implementing concurrent logic programming languages, developing formal models for automated reasoning, performance modelling parallel relational database systems, and visualisizing resources in shared web caches. His current research interests are in applications of collaborative virtual environments, parallel logic programming and networked computing technologies.     

A logic-based integration of active and deductive databases

A logic-based approach to the specification of active database functionality is presented which not only endows active databases with a well-defined and well-understood formal semantics, but also tightly integrates them with deductive databases. The problem of endowing deductive databases with rule-based active behaviour has been addressed in different ways. Typical approaches include accounting for active behaviour by extending the operational semantics of deductive databases, or, conversely, accounting for deductive capabilities by constraining the operational semantics of active databases. The main contribution of the paper is an alternative approach in which a class of active databases is defined whose operational semantics is naturally integrated with the operational semantics of deductive databases without either of them strictly subsuming the other. The approach is demonstrated via the formalization of the syntax and semantics of an active-rule language that can be smoothly incorporated into existing deductive databases, due to the fact that the standard formalization of deductive databases is reused, rather than altered or extended. One distinctive feature of the paper is its use of ahistory, as defined in the Kowalski-Sergot event-calculus, to define event occurrences, database states and actions on these. This has proved to be a suitable foundation for a comprehensive logical account of the concept set underpinning active databases. The paper thus contributes a logical perspective to the ongoing task of developing a formal theory of active databases. Alvaro Adolfo Antunes Fernandes, Ph.D.: He received a B.Sc. in Economics (Rio de Janeiro, 1984), an M.Sc. in Knowledge-Based Systems (Edinburgh, 1990) and a Ph.D. in Computer Science (Heriot-Watt, 1995). He worked as a Research Associate at Heriot-Watt University from December 1990 until December 1995. In January 1996 he joined the Department of Mathematical and Computing Sciences at Goldsmiths College, University of London, as a Lecturer. His current research interests include advanced data- and knowledge-base technology, logic programming, and software engineering. M. Howard Williams, Ph.D., D.Sc.: He obtained his Ph.D. in ionospheric physics and recently a D.Sc. in Computer Science. He was appointed as the first lecturer in Computer Science at Rhodes University in 1970. During the following decade he rose to Professor of Computer Science and in 1980 was appointed as Professor of Computer Science at Heriot-Watt University. From 1980 to 1988 he served as Head of Department and then as director of research until 1992. He is now head of the Database Research Group at Heriot-Watt University. His current research interests include active databases, deductive objectoriented databases, spatial databases, parallel databases and telemedicine. Norman W. Paton, Ph.D.: He received a B.Sc. in Computing Science from the University of Aberdeen in 1986. From 1986 to 1989 he worked as a Research Assistant at the University of Aberdeen, receiving a Ph. D. in 1989. From 1989 to 1995 he was a Lecturer in Computer Science at Heriot-Watt University. Since July 1995, he has been a Senior Lecturer in Department of Computer Science at the University of Manchester. His current research interests include active databases, deductive object-oriented databases, spatial databases and database interfaces.     

Constructive negation and constraint logic programming with sets

The aim of this paper is to extend theConstructive Negation technique to the case ofCLP(SεT), a Constraint Logic Programming (CLP) language based on hereditarily (and hybrid) finite sets. The challenging aspects of the problem originate from the fact that the structure on whichCLP(SεT) is based is notadmissible closed, and this does not allow to reuse the results presented in the literature concerning the relationships betweenCLP and constructive negation. We propose a new constraint satisfaction algorithm, capable of correctly handling constructive negation for large classes ofCLP(SεT) programs; we also provide a syntactic characterization of such classes of programs. The resulting algorithm provides a novel constraint simplification procedure to handle constructive negation, suitable to theories where unification admits multiple most general unifiers. We also show, using a general result, that it is impossible to construct an interpreter forCLP(SεT) with constructive negation which is guaranteed to work for any arbitrary program; we identify classes of programs for which the implementation of the constructive negation technique is feasible. Agostino Dovier, Ph.D.: He is a researcher in the Department of Science and Technology at the University of Verona, Italy. He obtained his master degree in Computer Science from the University of Udine, Italy, in 1991 and his Ph.D. in Computer Science from the University of Pisa, Italy, in 1996. His research interests are in Programming Languages and Constraints over complex domains, such as Sets and Multisets. He has published over 20 research papers in International Journals and Conferences. He is teaching a course entitled “Special Languages and Techniques for Programming” at the University of Verona. Enrico Pontelli, Ph.D.: He is an Assistant Professor in the Department of Computer Science at the New Mexico State University. He obtained his Laurea degree from the University of Udine (Italy) in 1991, his Master degree from the University of Houston in 1992, and his Ph.D. degree from New Mexico State University in 1997. His research interests are in Programming Languages, Parallel Processing, and Constraint Programming. He has published over 50 papers and served on the program committees of different conferences. He is presently the Associate Director of the Laboratory for Logic, Databases, and Advanced Programming. Gianfranco Rossi, Ph.D.: He received his degree in Computer Science from the University of Pisa in 1979. From 1981 to 1983 he was employed at Intecs Co. System House in Pisa. From November 1983 to February 1989 he was a researcher at the Dipartimento di Informatica of the University of Turin. Since March 1989 he is an Associate Professor of Computer Science, currently with the University of Parma. He is the author of several papers dealing mainly with programming languages, in particular logic programming languages and Prolog, and extended unification algorithms. His current research interests are (logic) programming languages with sets and set unification algorithms.     

Blackboard relations in the μLog coordination model

This paper describescoordination relations, that are relations that induce the presence or absence of data on some dataspaces from the presence or absence of other data on other dataspaces. To that end we build upon previous work on the μLog model and show that the coordination relations can be easily incorporated in it. This is achieved, on the one hand, by means of novel auxiliary operations, not classically used in Linda-like languages, and, on the other hand, by a translation technique reducing the extended μLog model to the core model augmented with the auxiliary operations. Among the most significant ones are multiple read and get operations on a blackboard, readall and getall operations, and tests for the absence of data on blackboards. Although simple, the form of coordination relations we propose is quite powerful as evidenced by a few examples including relations coming from the object-oriented paradigm such as inheritance relations. Jean-Marie Jacquet, Ph.D.: He is Professor at the Institute of Informatics at the University of Namur, Belgium, and, at an honorary title, Research Associate of the Belgian National Fund for Scientific Research. He obtained a Master in Mathematics from the University of Liège in 1982, a Master in Computer Science from the University of Namur in 1984 and a Ph.D. in Computer Science from the University of Namur in 1989. His research interest are in Programming Languages and Coordination models. He has served as a reviewer and program committee member of several conferences. Koen de Bosschere, Ph.D.: He holds the degree of master of Science in Engineering of the Ghent University, and a Ph.D. from the same University. He is currently research associate with the Fund for Scientific Research — Flanders and senior lecturer at the Ghent University, where he teaches courses on computer architecture, operating systems and declarative programming languages. His research interests are coordination in parallel logic programming, computer architecture and systems software.     

Inductive logic programming for relational knowledge discovery

Inductive logic programming (ILP) is concerned with the induction of logic programs from examples and background knowledge. In ILP, the shift of attention from program synthesis to knowledge discovery resulted in advanced techniques that are practically applicable for discovering knowledge in relational databases. This paper gives a brief introduction to ILP, presents selected ILP techniques for relational knowledge discovery and reviews selected ILP applications. Nada Lavrač, Ph.D.: She is a senior research associate at the Department of Intelligent Systems, J. Stefan Institute, Ljubljana, Slovenia (since 1978) and a visiting professor at the Klagenfurt University, Austria (since 1987). Her main research interest is in machine learning, in particular inductive logic programming and intelligent data analysis in medicine. She received a BSc in Technical Mathematics and MSc in Computer Science from Ljubljana University, and a PhD in Technical Sciences from Maribor University, Slovenia. She is coauthor of KARDIO: A Study in Deep and Qualitative Knowledge for Expert Systems, The MIT Press 1989, and Inductive Logic Programming: Techniques and Applications, Ellis Horwood 1994, and coeditor of Intelligent Data Analysis in Medicine and Pharmacology, Kluwer 1997. She was the coordinator of the European Scientific Network in Inductive Logic Programming ILPNET (1993–1996) and program cochair of the 8th European Machine Learning Conference ECML’95, and 7th International Workshop on Inductive Logic Programming ILP’97. Sašo Džeroski, Ph.D.: He is a research associate at the Department of Intelligent Systems, J. Stefan Institute, Ljubljana, Slovenia (since 1989). He has held visiting researcher positions at the Turing Institute, Glasgow (UK), Katholieke Universiteit Leuven (Belgium), German National Research Center for Computer Science (GMD), Sankt Augustin (Germany) and the Foundation for Research and Technology-Hellas (FORTH), Heraklion (Greece). His research interest is in machine learning and knowledge discovery in databases, in particular inductive logic programming and its applications and knowledge discovery in environmental databases. He is co-author of Inductive Logic Programming: Techniques and Applications, Ellis Horwood 1994. He is the scientific coordinator of ILPnet2, The Network of Excellence in Inductive Logic Programming. He was program co-chair of the 7th International Workshop on Inductive Logic Programming ILP’97 and will be program co-chair of the 16th International Conference on Machine Learning ICML’99. Masayuki Numao, Ph.D.: He is an associate professor at the Department of Computer Science, Tokyo Institute of Technology. He received a bachelor of engineering in electrical and electronics engineering in 1982 and his Ph.D. in computer science in 1987 from Tokyo Institute of Technology. He was a visiting scholar at CSLI, Stanford University from 1989 to 1990. His research interests include Artificial Intelligence, Global Intelligence and Machine Learning. Numao is a member of Information Processing Society of Japan, Japanese Society for Artificial Intelligence, Japanese Cognitive Science Society, Japan Society for Software Science and Technology and AAAI.     

Learning Horn definitions: Theory and an application to planning

A Horn definition is a set of Horn clauses with the same predicate in all head literals. In this paper, we consider learning non-recursive, first-order Horn definitions from entailment. We show that this class is exactly learnable from equivalence and membership queries. It follows then that this class is PAC learnable using examples and membership queries. Finally, we apply our results to learning control knowledge for efficient planning in the form of goal-decomposition rules. Chandra Reddy, Ph.D.: He is currently a doctoral student in the Department of Computer Science at Oregon State University. He is completing his Ph.D. on June 30, 1998. His dissertation is entitled “Learning Hierarchical Decomposition Rules for Planning: An Inductive Logic Programming Approach.” Earlier, he had an M. Tech in Artificial Intelligence and Robotics from University of Hyderabad, India, and an M.Sc.(tech) in Computer Science from Birla Institute of Technology and Science, India. His current research interests broadly fall under machine learning and planning/scheduling—more specifically, inductive logic programming, speedup learning, data mining, and hierarchical planning and optimization. Prasad Tadepalli, Ph.D.: He has an M.Tech in Computer Science from Indian Institute of Technology, Madras, India and a Ph.D. from Rutgers University, New Brunswick, USA. He joined Oregon State University, Corvallis, as an assistant professor in 1989. He is now an associate professor in the Department of Computer Science of Oregon State University. His main area of research is machine learning, including reinforcement learning, inductive logic programming, and computational learning theory, with applications to classification, planning, scheduling, manufacturing, and information retrieval.     

Early Estimation of Users’ Perception of Software Quality

This paper presents a methodology for estimating users’ opinion of the quality of a software product. Users’ opinion changes with time as they progressively become more acquainted with the software product. In this paper, we study the dynamics of users’ opinion and offer a method for assessing users’ final perception, based on measurements in the early stages of product release. The paper also presents methods for collecting users’ opinion and from the derived data, shows how their initial belief state for the quality of the product is formed. It adapts aspects of Belief Revision theory in order to present a way of estimating users’ opinion, subsequently formed after their opinion revisions. This estimation is achieved by using the initial measurements and without having to conduct surveys frequently. It reports the correlation that users tend to infer among quality characteristics and represents this correlation through a determination of a set of constraints between the scores of each quality characteristic. Finally, this paper presents a fast and automated way of forming users’ new belief state for the quality of a product after examining their opinion revisions. Dimitris Stavrinoudis received his degree in Computer Engineering from Patras University and is a Ph.D. student of Computer Engineering and Informatics Department. He worked as a senior computer engineer and researcher at the R.A. Computer Technology Institute. He has participated in research and development projects in the areas of software engineering, databases and educational technologies. Currently, he works at the Hellenic Open University. His research interests include software quality, software metrics and measurements. Michalis Xenos received his degree and Ph.D. in Computer Engineering from Patras University. He is a Lecturer in the Informatics Department of the School of Sciences and Technology of the Hellenic Open University. He also works as a researcher in the Computer Technology Institute of Patras and has participated in over 15 research and development projects in the areas of software engineering and IT development management. His research interests include, inter alia, Software Engineering and Educational Technologies. He is the author of 6 books in Greek and over 30 papers in international journals and conferences. Pavlos Peppas received his B.Eng. in Computer Engineering from Patras University (1988), and his Ph.D. in Computer Science from Sydney University (1994). He joined Macquarie University, Sydney, as a lecturer in September 1993, and was promoted to a senior lecturer in October 1998. In January 2000, he took up an appointment at Intrasoft, Athens, where he worked as a senior specialist in the Data Warehousing department. He joint Athens Information Technology in February 2003 as a senior researcher, and since November 2003 he is an associate professor at the Dept of Business Administration at the University of Patras. He also holds an adjunct associate professorship at the School of Computer Science and Engineering at the University of New South Wales. His research interests lie primarily within the area of Artificial Intelligence, and more specifically in logic-based approaches to Knowledge Representation and Reasoning with application in robotics, software engineering, organizational knowledge management, and the semantic web. Dimitris Christodoulakis received his degree in Mathematics from the University of Athens and his Ph.D. in Informatics from the University of Bonn. He was a researcher at the National Informatics Centre of Germany. He is a Professor and Vice President of Computer Engineering and Informatics Department of Patras University. Scientific Coordinator in many research and development projects in the followings sections: Knowledge and Data Base Systems, Very large volume information storage, Hypertext, Natural Language Technology for Modern Greek. Author and co-author in many articles published in international conferences. Editor in proceedings of conventions. Responsible for proofing tools development for Microsoft Corp. He is Vice Director in the Research Academic Computer Technology Institute (RACTI).     

Proving termination of GHC programs

A transformational approach for proving termination of parallel logic programs such as GHC programs is proposed. A transformation from GHC programs to term rewriting systems is developed; it exploits the fact that unifications in GHC-resolution correspond to matchings. The termination of a GHC program for a class of queries is implied by the termination of the resulting rewrite system. This approach facilitates the applicability of a wide range of termination techniques developed for rewrite systems in proving termination of GHC programs. The method consists of three steps: (a) deriving moding information from a given GHC program, (b) transforming the GHC program into a term rewriting system using the moding information, and finally (c) proving termination of the resulting rewrite system. Using this method, the termination of many benchmark GHC programs such as quick-sort, merge-sort, merge, split, fair-split and append, etc., can be proved. This is a revised and extended version of Ref. 12). The work was partially supported by the NSF Indo-US grant INT-9416687 Kapur was partially supported by NSF Grant nos. CCR-8906678 and INT-9014074. M. R. K. Krishna Rao, Ph.D.: He currently works as a senior research fellow at Griffith University, Brisbane, Australia. His current interests are in the areas of logic programming, modular aspects and noncopying implementations of term rewriting, learning logic programs from examples and conuterexamples and dynamics of mental states in rational agent architectures. He received his Ph.D in computer science from Tata Institute of Fundamental Research (TIFR), Bombay in 1993 and worked at TIFR and Max Planck Institut für Informatik, Saarbrücken until January 1997. Deepak Kapur, Ph.D.: He currently works as a professor at the State University of New York at Albany. His research interests are in the areas of automated reasoning, term rewriting, constraint solving, algebraic and geometric reasoning and its applications in computer vision, symbolic computation, formal methods, specification and verification. He obtained his Ph.D. in Computer Science from MIT in 1980. He worked at General Electric Corporate Research and Development until 1987. Prof. Kapur is the editor-in-chief of the Journal of Automated Reasoning. He also serves on the editorial boards of Journal of Logic Programming, Journal on Constraints, and Journal of Applicable Algebra in Engineering, Communication and Computer Science. R. K. Shyamasundar, Ph.D.: He currently works as a professor at Tata Institute of Fundamental Research (TIFR), Bombay. His current intersts are in the areas of logic programming, reactive and real time programming, constraint solving, formal methods, specification and verification. He received his Ph.D in computer science from Indian Institute of Science, Bangalore in 1975 and has been a faculty member at Tata Institute of Fundamental Research since then. He has been a visiting/regular faculty member at Technological University of Eindhoven, University of Utrecht, IBM TJ Watson Research Centre, Pennsylvania State University, University of Illinois at Urbana-Champaign, INRIA and ENSMP, France. He has served on (and chaired) Program Committees of many International Conferences and has been on the Editorial Committees.     

Verification of distributed programs using representative interleaving sequences

Summary We present a formal proof method for distributed programs. The semantics used to justify the proof method explicitly identifies equivalence classes of execution sequences which are equivalent up to permuting commutative operations. Each equivalence class is called an interleaving set or a run. The proof rules allow concluding the correctness of certain classes of properties for all execution sequences, even though such properties are demonstrated directly only for a subset of the sequences. The subset used must include a representative sequence from each interleaving set, and the proof rules, when applicable, guarantee that this is the case. By choosing a subset with appropriate sequences, simpler intermediate assertions can be used than in previous formal approaches. The method employs proof lattices, and is expressed using the temporal logic ISTL. Shmuel Katz received his B.A. in Mathematics and English Literature from U.C.L.A., and his M.Sc. and Ph.D. in Computer Science (1976) from the Weizmann Institute in Rechovot, Israel. From 1976 to 1981 he was at the IBM Israel Scientific Center. Presently, he is on the faculty of the Computer Science Department at the Technion in Haifa, Israel. In 1977–1978 he visited for a year at the University of California, Berkeley, and in 1984–1985 was at the University of Texas at Austin. He has been a consultant and visitor at the MCC Software Technology Program, and in 1988–1989 was a visiting scientist at the I.B.M. Watson Research Center. His research interests include the methodology of programming, specification methods, program verification and semantics, distributed programming, data structures, and programming languages. Doron Peled was born in 1962 in Haifa. He received his B.Sc. and M.Sc. in Computer Science from the Technion, Israel in 1984 and 1987, respectively. Between 1987 and 1991 he did his military service. He also completed his D.Sc. degree in the Technion during these years. Dr. Peled was with the Computer Science department at Warwick University in 1991–1992. He is currently a member of the technical staff with AT & T Bell Laboratories. His main research interests are specification and verification of programs, especially as related to partial order models, fault-tolerance and real-time. He is also interested in semantics and topology.This research was carried out while the second author was at the Department of Computer Science, The Technion, Haifa 32000, Israel     

On the completeness of naive memoing in Prolog

Memoing is often used in logic programming to avoid redundant evaluation of similar goals, often on programs that are inherently recursive in nature. The interaction between memoing and recursion, however, is quite complex. There are several top-down evaluation strategies for logic programs that utilize memoing to achieve completeness in the presence of recursion. This paper’s focus, however, is on the use ofnaive memoing in Prolog. Using memoingnaively in conjunction with recursion in Prolog may not produce expected results. For example, adding naive memoing to Prolog’s evaluation of a right-recursive transitive closure may be incomplete, whereas adding naive memoing to Prolog’s evaluation of a left-recursive transitive closure may be terminating and complete. This paper examines the completeness of naive memoing in linear-recursive, function-free logic programs evaluated with Prolog’s top-down evaluation strategy. In addition, we assume that the program is definite and safe, having finite base relations and exactly one recursive predicate. The goal of the paper is a theoretical study of the completeness of naive memoing and recursion in Prolog, illustrating the limitations imposed even for this simplified class of programs. The naive memoing approach utilized for this study is based on extension tables, which provide a memo mechanism with immediate update view semantics for Prolog programs, through a source transformation known as ET. We introduce the concept ofET-complete, which refers to the completeness of the evaluation of a query over a Prolog program that memos selected predicates through the ET transformation. We show that left-linear recursions defined by a single recursive rule are ET-complete. We generalize the class of left-linear recursions that are ET-complete by introducing pseudo-left-linear recursions, which are also defined by a single linear recursive rule. To add left-linear recursions defined bymultiple linear recursive rules to the class of ET-complete recursions, we present a left-factoring algorithm that converts left-linear recursions defined by multiple recusive rules into pseudo-left-linear recursions defined by a single recursive rule. Based on these results, the paper concludes by identifying research directions for expanding the class of Prolog programs to be examined in future work. This work was partially supported by the National Science Foundation under Grant CCR-9008737. Suzanne Wagner Dietrich, Ph.D.: She is an Associate Professor in the Department of Computer Science and Engineering at Arizona State University. Her research emphasis is on the evaluation of declarative logic programs especially in the context of deductive databases, including materialized view maintenance and condition monitoring in active deductive databases. More recently, her research interests include the integration of active, object-oriented and deductive databases as well as the application of this emerging database technology to various disciplines such as software engineering. She received the B. S. degree in computer science in 1983 from the State University of New York at Stony Brook, and as the recipient of an Office of Naval Research Graduate Fellowship, earned her Ph.D. degree in computer science at Stony Brook in 1987. Changguan Fan, M.S.: He is a Ph.D. candidate in the Department of Computer Science and Engineering at Arizona State University and a software engineer at the Regenisys Corporation in Scottsdale, AZ. His research interests include the evaluation of logic programs, deductive database systems and database management systems. He received his B.S. in Computer Science from the Shanghai Institute of Railway Technology, Shanghai, China in 1982 and his M.S. in the Department of Computer Science and Engineering at Arizona State University in 1989.     

A distributable security management architecture for enterprise systems spanning multiple security domains

Administering security in modern enterprise systems may prove an extremely complex task. Their large scale and dynamic nature are the main factors that contribute to this fact. A robust and flexible model is needed in order to guarantee both the easy management of security information and the efficient implementation of security mechanisms. In this paper, we present the foundations and the prototypical implementation of a new access control framework. The framework is mainly targeted to highly dynamic, large enterprise systems (e.g., service provisioning platforms, enterprise portals etc.), which contain various independent functional entities. Significant advantages gained from the application of the designated framework in such systems are epitomized in the easiness of managing access to their hosted resources (e.g., services) and the possibility of applying distributable management schemes for achieving it. The proposed framework allows for multi-level access control through the support of both role-based and user-based access control schemes. Discussion is structured in three distinct areas: the formal model of the proposed framework, the data model for supporting its operation, and the presentation of a prototypical implementation. The development of the framework is based on open technologies like XML, java and Directory Services. At the last part of the paper the results of a performance assessment are presented, aiming to quantify the delay overhead, imposed by the application of the new framework in a real system. Ioannis Priggouris received his B.Sc. in Informatics from the Department of Informatics & Telecommunications of the University of Athens, Greece in 1997 and his M.Sc. in Communication Systems and Data Networks from the same Department in 2000. Over the last years he has been a PhD candidate in the department. Since 1999, he has been a member of the Communication Networks Laboratory (CNL) of the University of Athens. As a senior researcher of the CNL he has participated in several EU projects implemented in the context of IST, namely the EURO-CITI and the PoLoS projects. He has also been extensively involved in several National IT Research projects. His research interests are in the areas of mobile computing, QoS and mobility support for IP networks, and network security. He is the author of several papers and book chapters in the aforementioned areas. Stathes Hadjiefthymiades received his B.Sc. (honors) and M.Sc. in Informatics from the Dept. of Informatics, University of Athens, Greece, in 1993 and 1996 respectively. In 1999 he received his Ph.D. from the University of Athens (Dept. of Informatics and Telecommunications). In 2002 he received a joint engineering-economics M.Sc. from the National Technical University of Athens. In 1992 he joined the Greek consulting firm Advanced Services Group, Ltd., where he was involved in the analysis, design and implementation of telematic applications and other software systems. In 1995 he joined, as research engineer, the Communication Networks Laboratory (UoA-CNL) of the University of Athens. During the period September 2001-July 2002, he served as a visiting assistant professor at the University of Aegean, Dept. of Information and Communication Systems Engineering. On the summer of 2002 he joined the faculty of the Hellenic Open University (Dept. of Informatics), Patras, Greece, as an assistant professor. Since December 2003, he is in the faculty of the Dept. of Informatics and Telecommunications, University of Athens, where he is presently an assistant professor and coordinator of the Pervasive Computing Research Group. He has participated in numerous projects realized in the context of EU programs (ACTS, ORA, TAP, and IST), EURESCOM projects, as well as national initiatives. His research interests are in the areas of web engineering, wireless/mobile computing, and networked multimedia applications. He is the author of over 100 publications in the above areas.     

A platform for virtual collaboration spaces and educational communities: the case of EVE

This paper presents the design, implementation and evaluation of EVE Community Prototype, which is an educational virtual community aiming to meet the requirements of a Virtual Collaboration Space and to support e-learning services. Furthermore, this paper describes the design and implementation of an integrated platform for Networked Virtual Environments, called EVE Platform, which supports the afore-mentioned educational community. This platform supports stable event sharing and creation of multi-user three dimensional (3D) places, H.323-based voice over IP services integrated in 3D spaces as well as multiple concurrent virtual worlds. Christos Bouras obtained his Diploma and PhD from the Department Of Computer Engineering and Informatics of Patras University (Greece). He is currently an Associate Professor in the above department. Also he is a scientific advisor of Research Unit 6 in Research Academic Computer Technology Institute (CTI), Patras, Greece. His research interests include Analysis of Performance of Networking and Computer Systems, Computer Networks and Protocols, Telematics and New Services, QoS and Pricing for Networks and Services, e-Learning Networked Virtual Environments and WWW Issues. He has extended professional experience in Design and Analysis of Networks, Protocols, Telematics and New Services. He has published 200 papers in various well-known refereed conferences and journals. He is a co-author of seven books in Greek. He has been a PC member and referee in various international journals and conferences. He has participated in R&D projects such as RACE, ESPRIT, TELEMATICS, EDUCATIONAL MULTIMEDIA, ISPO, EMPLOYMENT, ADAPT, STRIDE, EUROFORM, IST, GROWTH and others. Also he is member of experts in the Greek Research and Technology Network (GRNET), Advisory Committee Member to the World Wide Web Consortium (W3C), Member of WG3.3 and WG6.4 of IFIP, Task Force for Broadband Access in Greece, ACM, IEEE, EDEN, AACE and New York Academy of Sciences. Eleftheria Giannaka obtained her Diploma from the Informatics Department of the Aristotelian University of Thessaloniki (Greece) and her Masters Degree from the Computer Engineering and Informatics Department of Patras University. She is currently a PhD Candidate of the Department of Computer Engineer and Informatics of Patras University. Furthermore, she is working as an R&D Computer Engineer at the Research Unit 6 of the Computer Technology Institute in Patra (Greece). Her interests include Computer Networks, Virtual Networks, System Architecture, Internet Applications, Electronic Commerce, Database Implementation and Administration, Virtual Reality applications, Performance Evaluation and Programming. Alexandros Panagopoulos was born in Pyrgos, Greece, 1981. He obtained his Diploma, from the Computer Engineering and Informatics Department of Patras University (Greece). In 2000 he became a member of Research Unit 6 of the Computer Technology Institute (CTI). His interests include Computer Networks, Multiuser Virtual Environments, Telematics, and C/C++ and Java programming. Dr. Thrasyvoulos Tsiatsos obtained his Diploma, his Master's Degree and his PhD from the Computer Engineering and Informatics Department of Patras University (Greece). He is currently an R&D Computer Engineer at the Research Unit 6 of Computer Technology Institute, Patras, Greece. His research interests include Computer Networks, Telematics, Distributed Systems, Networked Virtual Environments, Multimedia and Hypermedia. More particular he is engaged in Distant Education with the use of Computer Networks, Real Time Protocols and Networked Virtual Environments. He has published nine papers in journals and 30 papers in well-known refereed conferences. He has participated in R&D projects such as OSYDD, RTS-GUNET, ODL-UP, VES, ODL-OTE, INVITE, VirRAD and EdComNet.     

On semantic resolution with lemmaizing and contraction and a formal treatment of caching

Reducing redundancy in search has been a major concern for automated deduction. Subgoal-reduction strategies, such as those based on model elimination and implemented in Prolog technology theorem provers, prevent redundant search by usinglemmaizing andcaching, whereas contraction-based strategies prevent redundant search by usingcontraction rules, such assubsumption. In this work we show that lemmaizing and contraction can coexist in the framework ofsemantic resolution. On the lemmaizing side, we define two meta-level inference rules for lemmaizing in semantic resolution, one producing unit lemmas and one producing non-unit lemmas, and we prove their soundness. Rules for lemmaizing are meta-rules because they use global knowledge about the derivation, e.g. ancestry relations, in order to derive lemmas. Our meta-rules for lemmaizing generalize to semantic resolution the rules for lemmaizing in model elimination. On the contraction side, we give contraction rules for semantic strategies, and we define apurity deletion rule for first-order clauses that preserves completeness. While lemmaizing generalizes success caching of model elimination, purity deletion echoes failure caching. Thus, our approach integrates features of backward and forward reasoning. We also discuss the relevance of our work to logic programming. Supported in part by the National Science Foundation with grant CCR-94-08667 and CCR-97-01508. Supported in part by grant NSC 86-2213-E-002-047 and NSC 87-2213-E-002-029 of the National Science Council of the Republic of China. Maria Paola Bonacina, Ph.D.: She is on the faculty of the Department of Computer Science of the University of Iowa. She received a laurea (1986) and a doctorate in informatics from the Universita degli Studi di Milano, and a Ph.D. in computer science from the State University of New York at Stony Brook (1992). She was awarded fellowships by the Universita degli Studi di Milano, the European Union and the General Electric Foundation. The unifying theme of her research is automated theorem proving. Her research areas include distributed automated deduction, the theory of search and strategy analysis, completion-based theorem proving, category theory for computer science, term rewriting systems, logic programming, and manyvalued logic. Jieh Hsiang, Ph.D.: He is a Professor of Computer Science at the National Taiwan University and is also the Director of the Center of Excellence for Research in Computer Systems of the National Taiwan University. Professor Hsiang is known for work in term rewriting systems and automated deduction. His other research interests include logic programming, programming logics, computer viruses, and intelligent agents. Recently he has also become interested in the digitization of Taiwanese and Chinese historical records and heritage. Professor Hsiang received a B.S. degree in mathematics from National Taiwan University in 1976 and a Ph.D. degree in computer science from the University of Illinois at Urbana-Champaign in 1982. Before returning to Taiwan in 1993, he was a Professor of Computer Science at the State University of New York st Stony Brook.     

Cautious induction: An alternative to clause-at-a-time hypothesis construction in inductive logic programming

Hypotheses constructed by inductive logic programming (ILP) systems are finite sets of definite clauses. Top-down ILP systems usually adopt the following greedy clause-at-a-time strategy to construct such a hypothesis: start with the empty set of clauses and repeatedly add the clause that most improves the quality of the set. This paper formulates and analyses an alternative method for constructing hypotheses. The method, calledcautious induction, consists of a first stage, which finds a finite set of candidate clauses, and a second stage, which selects a finite subset of these clauses to form a hypothesis. By using a less greedy method in the second stage, cautious induction can find hypotheses of higher quality than can be found with a clause-at-a-time algorithm. We have implemented a top-down, cautious ILP system called CILS. This paper presents CILS and compares it to Progol, a top-down clause-at-a-time ILP system. The sizes of the search spaces confronted by the two systems are analysed and an experiment examines their performance on a series of mutagenesis learning problems. Simon Anthony, BEng.: Simon, perhaps better known as “Mr. Cautious” in Inductive Logic Programming (ILP) circles, completed a BEng in Information Engineering at the University of York in 1995. He remained at York as a research student in the Intelligent Systems Group. Concentrating on ILP, his research interests are Cautious Induction and developing number handling techniques using Constraint Logic Programming. Alan M. Frisch, Ph.D.: He is the Reader in Intelligent Systems at the University of York (UK), and he heads the Intelligent Systems Group in the Department of Computer Science. He was awarded a Ph. D. in Computer Science from the University of Rochester (USA) in 1986 and has held faculty positions at the University of Sussex (UK) and the University of Illinois at Urbana-Champaign (USA). For over 15 years Dr. Frisch has been conducting research on a wide range of topics in the area of automated reasoning, including knowledge retrieval, probabilistic inference, constraint solving, parsing as deduction, inductive logic programming and the integration of constraint solvers into automated deduction systems.     

Inference of abduction theories for handling incompleteness in first-order learning

In real-life domains, learning systems often have to deal with various kinds of imperfections in data such as noise, incompleteness and inexactness. This problem seriously affects the knowledge discovery process, specifically in the case of traditional Machine Learning approaches that exploit simple or constrained knowledge representations and are based on single inference mechanisms. Indeed, this limits their capability of discovering fundamental knowledge in those situations. In order to broaden the investigation and the applicability of machine learning schemes in such particular situations, it is necessary to move on to more expressive representations which require more complex inference mechanisms. However, the applicability of such new and complex inference mechanisms, such as abductive reasoning, strongly relies on a deep background knowledge about the specific application domain. This work aims at automatically discovering the meta-knowledge needed to abduction inference strategy to complete the incoming information in order to handle cases of missing knowledge. Floriana Esposito received the Laurea degree in electronic Physics from the University of Bari, Italy, in 1970. Since 1994 is Full Professor of Computer Science at the University of Bari and Dean of the Faculty of Computer Science from 1997 to 2002. She founded and chairs the Laboratory for Knowledge Acquisition and Machine Learning of the Department of Computer Science. Her research activity started in the field of numerical models and statistical pattern recognition. Then her interests moved to the field of Artificial Intelligence and Machine Learning. The current research concerns the logical and algebraic foundations of numerical and symbolic methods in machine learning with the aim of the integration, the computational models of incremental and multistrategy learning, the revision of logical theories, the knowledge discovery in data bases. Application include document classification and understanding, content based document retrieval, map interpretation and Semantic Web. She is author of more than 270 scientific papers and is in the scientific committees of many international scientific Conferences in the field of Artificial Intelligence and Machine Learning. She co-chaired ICML96, MSL98, ECML-PKDD 2003, IEA-AIE 2005, ISMIS 2006. Stefano Ferilli was born in 1972. After receiving his Laurea degree in Information Science in 1996, he got a Ph.D. in Computer Science at the University of Bari in 2001. Since 2002 he is an Assistant Professor at the Department of Computer Science of the University of Bari. His research interests are centered on Logic and Algebraic Foundations of Machine Learning, Inductive Logic Programming, Theory Revision, Multi-Strategy Learning, Knowledge Representation, Electronic Document Processing and Digital Libraries. He participated in various National and European (ESPRIT and IST) projects concerning these topics, and is a (co-)author of more than 80 papers published on National and International journals, books and conferences/workshops proceedings. Teresa M.A. Basile got the Laurea degree in Computer Science at the University of Bari, Italy (2001). In March 2005 she discussed a Ph.D. thesis in Computer Science at the University of Bari titled “A Multistrategy Framework for First-Order Rules Learning.” Since April 2005, she is a research at the Computer Science Department of the University of Bari working on methods and techniques of machine learning for the Semantic Web. Her research interests concern the investigation of symbolic machine learning techniques, in particular of the cooperation of different inferences strategies in an incremental learning framework, and their application to document classification and understanding based on their semantic. She is author of about 40 papers published on National and International journals and conferences/workshops proceedings and was/is involved in various National and European projects. Nicola Di Mauro got the Laurea degree in Computer Science at the University of Bari, Italy. From 2001 he went on making research on machine learning in the Knowledge Acquisition and Machine Learning Laboratory (LACAM) at the Department of Computer Science, University of Bari. In March 2005 he discussed a Ph.D. thesis in Computer Science at the University of Bari titled “First Order Incremental Theory Refinement” which faces the problem of Incremental Learning in ILP. Since January 2005, he is an assistant professor at the Department of Computer Science, University of Bari. His research activities concern Inductive Logic Programming (ILP), Theory Revision and Incremental Learning, Multistrategy Learning, with application to Automatic Document Processing. On such topics HE is author of about 40 scientific papers accepted for presentation and publication on international and national journals and conference proceedings. He took part to the European projects 6th FP IP-507173 VIKEF (Virtual Information and Knowledge Environment Framework) and IST-1999-20882 COLLATE (Collaboratory for Annotation, Indexing and Retrieval of Digitized Historical Archive Materials), and to various national projects co-funded by the Italian Ministry for the University and Scientific Research.     

A program specialiser for meta-level compositions of logic programs

Metal-level compositions of object logic programs are naturally implemented by means of meta-programming techniques. Metainterpreters defining program compositions however suffer from a computational overhead that is due partly to the interpretation layer present in all meta-programs, and partly to the specific interpretation layer needed to deal with program compositions. We show that meta-interpreters implementing compositions of object programs can be fruitfully specialised w.r.t. meta-level queries of the form Demo (E, G), where E denotes a program expression and G denotes a (partially instantiated) object level query. More precisely, we describe the design and implementation of declarative program specialiser that suitably transforms such meta-interpreters so as to sensibly reduce — if not to completely remove — the overhead due to the handling of program compositions. In many cases the specialiser succeeds in eliminating also the overhead due to meta-interpretation. Antonio Brogi, Ph.D.: He is currently assistant professor in the Department of Computer Science at the University of Pisa, Italy. He received his Laurea Degree in Computer Science (1987) and his Ph. D. in Computer Science (1993) from the University of Pisa. His research interests include programming language design and semantics, logic programming, deductive databases, and software coordination. Simone Contiero: He is currently a Ph. D. student at the Department of Computer Science, University of Pisa (Italy). He received his Laurea Degree in Computer Science from the University of Pisa in 1994. His research interests are in high-level programming languages, metaprogramming and logic-based coordination of software.     

A Prolog simulator for deterministic P systems with active membranes

In this paper we propose a new way to represent P systems with active membranes based on Logic Programming techniques. This representation allows us to express the set of rules and the configuration of the P system in each step of the evolution as literals of an appropriate language of first order logic. We provide a Prolog program to simulate, the evolution of these P systems and present some auxiliary tools to simulate the evolution of a P system with active membranes using 2-division which solves the SAT problem following the techniques presented in Reference.¹⁰ Andrés Cordón-Franco: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Mathematical Logic, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical (software implementation) point of view. Miguel A. Gutiérrez-Naranjo: He is an assistant professor in the Computer Science and Artificial Intelligence Department at University of Sevilla, Spain. He is also a member of the Research Group on Natural Computing of the University of Seville. His research interest includes Machine Learning, Logic Programming and Membrane Computing, both from a theoretical and a practical point of view. Mario J. Pérez-Jiménez, Ph.D.: He is professor of Department of Computer Science and Artificial Intelligence at University of Seville, where he is the head of the Group of Research on Natural Computing, He has published 8 books of Mathematics and Computation, and more than 90 scientific articles in prestigious scientific journals. He is member of European Molecular Computing Consortium. Fernando Sancho-Caparrini: He is a member of the Department of Computer Science and Artificial Intelligence at the University of Sevilla (Spain). He is also a member of the research group on Natural Computing of the University of Seville. His research interest includes Complex Systems, DNA Computing, Logic in Computer Science, and Membrane Computing, both from a theoretical and from a practical point of view.     

Determination of user interfaces in adaptive systems using a rough classification-based method

This paper presents a novel method for user classification in adaptive systems based on rough classification. Adaptive systems could be used in many areas, for example in a user interface construction or e-Learning environments for learning strategy selection. In this paper the adaptation of web-based system user interface is presented. The goal of rough user classification is to select the most essential attributes and their values that group together users who are very much alike concerning the system logic. In order to group users we exploit their usage data taken from the user model of the adaptive web-based system user interface. We presented three basic problems for attribute selection that generates the following partitions: that is included, that includes and that is the closest to the given partition. Ngoc Thanh Nguyen, Ph.D., D.Sc.: He currently works as an associate professor at the Faculty of Computer Science and Management, Wroclaw University of Technology in Poland. He received his diplomas of M.Sc, Ph.D. and D.Sc. in Computer Science in 1986, 1989 and 2002, respectively. Actually, he is working on intelligent technologies for conflict resolution and inconsistent knowledge processing and e-learning methods. His teaching interests consist of database systems and distributed systems. He is a co-editor of 4 special issues in international journals, author of 3 monographs, editor of one book and about 110 other publications (book chapters, journal and refereed conference papers). He is an associate editor of the following journals: “International Journal of Computer Science & Application”; “Journal of Information Knowledge System Management”; and “International Journal of Knowledge-Based & Intelligent Engineering Systems”. He is a member of societies: ACM, IFIP WG 7.2, ISAI, KES International, and WIC. Janusz Sobecki, Ph.D.: He is an Assistant Professor in Institute of Applied Informatics (IAI) at Wroclaw University of Technology (WUT). He received his M. Sc. in Computer Science from Faculty of Computer Science and Management at WUT in 1986 and Ph.D. in Computer Science from Faculty of Electronics at WUT in 1994. For 1986–1996 he was an Assistant at the Department of Information Systems (DIS) at WUT. For 1988–1996 he was also a head of the laboratory at DIS. For 1996–2004 he was an Assistant Professor in DIS and since fall of 2004 at IAI, both at WUT. His research interests include information retrieval, multimedia information systems, system usability and recommender systems. He is on the editorial board of New Generation Computing and was a co-editor of two journal special issues. He is a member of American Association of Machinery.