João P. Martins

Ontologies: How can They be Built?

Ontologies are an important component in many areas, such as knowledge management and organization, electronic commerce and information retrieval and extraction. Several methodologies for ontology building have been proposed. In this article, we provide an overview of ontology building. We start by characterizing the ontology building process and its life cycle. We present the most representative methodologies for building ontologies from scratch, and the proposed techniques, guidelines and methods to help in the construction task. We analyze and compare these methodologies. We describe current research issues in ontology reuse. Finally, we discuss the current trends in ontology building and its future challenges, namely, the new issues for building ontologies for the Semantic Web.

SNePSwD: A newcomer to the SNePS family

Abstract SNePS 2.1 is a knowledge representation and reasoning system that records the dependencies among propositions that are needed to perform a revision of beliefs when a contradiction is detected. The reasoning of SNePS 2.1 is based on a monotonic logic and the system has no provisos for performing an automatic revision of beliefs. In this paper we present SNePSwD that extends the capabilities of SNePS 2.1 along two dimensions: (1) it is able to represent default rules and to perform default reasoning, i.e. the logic underlying SNePSwD is non-monotonic; (2) it accepts the specification of preferences between hypotheses and uses them to decide which hypotheses to discard to resolve a contradiction. This latter possibility allows a semi-automatic contradiction resolution (in some cases, even completely automatic). We discuss the motivations for the creation of SNePSwD, present the form of default rules it uses, discuss the meaning of each of the three kinds of consequence, and describe how preferences ...

Scheduling and managing crew in the Portuguese railways

Abstract We present a tool to generate applications in crew scheduling. The first application developed with this tool, called “ESCALAS”, schedules crews for the Portuguese Railways (it schedules both driving and other crew). This application is complete and installed in the Portuguese Railways. The application is presently undergoing extensive testing and has proved to produce schedules that are comparable with those produced by human experts, at a fraction of time. The system is planned to enter routine operation in May 1992. The system uses a graphic, highly intuitive interface, and enables four different modes of operation: (1) Manual operation, in which the user makes the decisions in building the schedule and the system automatically verifies all the constraints and labour rules imposed upon it; (2) Semiautomatic operation, in which the system gives hints about hoe the user should pursue the schedule; (3) Fully automatic operation, in which thesystem automatically builds a schedule, according to a predefined set of scheduling strategies; (4) Mixed mode, in which there is an interaction with the user who may impose certain restrictions or combinations of tasks, the systems partially builds a schedule which can then be modified by the user and the automatic generation may proceed with the restrictions imposed. Besides, the system is able to perform crew assignment to each one of the schedules produced and can modify both the schedule and the assignment produced.

Permissive Belief Revision

We propose a new operation of belief revision, called permissive belief revision. The underlying idea of permissive belief revision is to replace the beliefs that are abandoned by traditional theories with weaker ones, entailed by them, that still keep the resulting belief set consistent. This framework allows us to keep more beliefs than what is usual using existent belief base-based revision theories.

How to change your mind

In this paper, we investigate the rules that should underlie a computer program that is capable of revising its beliefs or opinions. Such a program maintains a model of its environment, which is updated to reflect perceived changes in the environment. This model is stored in a knowledge base, and the program draws logical inferences from the information in the knowledge base. All the inferences drawn are added to the knowledge base. Among the propositions in the knowledge base, there are some in which the program believes, and there may be others in which the program does not believe. Inputs from the outside world or reasoning carried out by the program may lead to the detection of contradictions, in which case the program has to revise its beliefs in order to get rid of the contradiction and to accommodate the new information.

Recent advances and developments—the SNePS 2.11 report

In this paper, we describe those features that distinguish SNePS 2.1 from earlier versions of SNePS. These include: contexts; belief spaces; the knowledge debugger; the graphics package; and the elimination of duplicated reports. We also describe the SNePS 2.1 versions of path-based inference and SNePSLOG, and, finally, we indicate areas of SNePS 2.1 that still need work.

NMR molecular dynamics study of chromonic liquid crystals Edicol Sunset Yellow doped with salts

We investigate the effect of monoatomic salts on the molecular dynamics in the nematic and isotropic phases formed by the chromonic liquid crystal Edicol Sunset Yellow. The study was carried out using proton nuclear magnetic resonance relaxometry. To analyse the effect of incorporation of additional sodium chloride or lithium chloride on the solutions’ molecular dynamics, the spin‐lattice relaxation time was measured for Larmor frequencies between 10kHz and 100MHz. In the nematic phase, the presence of additional sodium or lithium ions seems to contribute to an increase of the rotations/reorientations correlation times in comparison with the mixture without extra ions. The collective motions detected by proton NMR relaxometry are associated with collective fluctuations of molecules within the stacks in the nematic phase and with order parameter fluctuations in the isotropic phase. Copyright

The STRICT assumption: a propositional approach to change

Abstract There are two main approaches to reasoning about change, the logicist—relying on the assumption that if actions and situations can be represented as propositions, then reasoning about change is nothing but classical reasoning— and the non-logicist—based on the assumption that the effects of actions are circumscribed to the ones explicitly stated in the corresponding operator descriptions, everything else remaining unaffected by change (STRIPS assumption). Both of these approaches have pitfalls: the former rely on associating the state of the world with a situation variable, which implies the need to write down frame axioms, stating what characteristics of the world are not affected by change. The latter assumes that the only characteristics of the world that can change are those which correspond to direct observation and not those derived using inference. That is to say, operators must be characterized using only ‘basic’ or ‘primitive’ predicates. The direct consequences of these pitfalls are, on...

A Unified Approach to Default Reasoning and Belief Revision

We present a unified approach to three important areas of AI: nonmonotonic logics, belief revision theories, and belief revision systems. The nonmonotonic logic we present, SWMC, is appropriate to support belief revision systems, because it keeps a track of dependencies between formulas. Another distinguishing feature of SWMC is the distinction between what follows soundly from a set of premises, and what can plausibly be concluded. In what concerns belief revision theories, we present a theory based on a nonmonotonic logic, SWMC, which, to the best of our knowledge, is a novel approach. Finally, we use an implementation of a belief revision system based on the logic and the belief revision theory, to illustrate these formalisms.

Expanding SNePS Capabilities with LORE

We briefly describe LORE, a logic with four values, the traditional truth values T and F, and two “Unknown” values, allowing to differentiate between knowing that nothing is known, and not knowing (with the available resources) whether it is known. A computer system based on LORE has the capability to remember all the paths followed during an attempt to answer a question. For each path, it records the used hypotheses (the hypotheses that constitute the path), the missing hypotheses (when the path did not lead to an answer), and why they were assumed missing. A number of examples of the use of LORE are discussed, and it is shown that SNePS capabilities can be expanded if LORE is accepted as the logic underlying its inferences.