User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of the alignments produced by automated alignment algorithms. In this paper, we present a broad study on user validation of ontology alignments that encompasses three distinct but inter-related aspects: the profile of the user, the services of the alignment system, and its user interface. We discuss key issues pertaining to the alignment validation process under each of these aspects and provide an overview of how current systems address them. Finally, we use experiments from the Interactive Matching track of the Ontology Alignment Evaluation Initiative 2015–2018 to assess the impact of errors in alignment validation, and how systems cope with them as function of their services.

Engineering knowledge is a specific kind of knowledge that is oriented to the production of particular classes of artifacts, is typically related to disciplined design methods, and takes place in tool-intensive contexts. As a consequence, representing engineering knowledge requires the elaboration of complex models that combine functional and structural representations of the resulting artifacts with process and methodological knowledge. The different categories used in the engineering domain vary in their status and in the way they should be manipulated when building applications that support engineering processes. These categories include artifacts, activities, methods and models. This paper surveys existing models of engineering knowledge and discusses an upper ontology that abstracts the categories that crosscut different engineering domains. Such an upper model can be reused for particular engineering disciplines. The process of creating such elaborations is reported on the particular case study of Software Engineering as a concrete application example.

Analysis and design of Information Systems (ISs) is the process of eliciting the system's requirements and transforming them into a model that can be used to develop ISs. Analysis and design of Agent-Oriented Information Systems (AOISs) relates to the very same process using the multi-agent paradigm. A comprehensive and rigorous methodology for developing multi-agent systems is lacking (Elammari & Lalonde, 1999; Odell et al., 2000). Most existing multi-agent systems were developed in an ad-hoc manner, and systems developers paid little attention to requirements specification and the analysis process (Treur, 1999a).

The paper has two goals: (a) to provide an overview and (b) to discuss challenges and future research of the field. To address the first goal, we review different methodologies that are suitable for analysing and designing AOIS. This is done by examining, for each methodology, its suitability in supporting the early phases of the software engineering process (specifically analysis and design) as well as its capabilities for modelling agent-oriented systems. To address the second goal, we analyse the limitations of existing approaches, identify critical issues and point to what we think are possible future directions.

This commentary describes notable commercial applications of case-based reasoning, including systems that have been in continuous profitable use for over a decade. It is divided into sections on engineering applications, helpdesk applications and on-line case-based reasoning.

The popularity of smart cars is increasing around the world as they offer a wide range of services and conveniences. These smart cars are equipped with a variety of sensors generating a large amount of data, many of which are critical. Besides, there are multiple parties involved in the lifespan of a smart car, such as manufacturers, car owners, government agencies, and third-party service providers who also generate data about the vehicle. In addition to managing and sharing data among these entities in a secure and privacy-friendly way which is a great challenge itself, there exists a trust deficit about some types of data as they remain under the custody of the car owner (e.g. satellite navigation and mileage data) and can easily be manipulated. In this article, we propose a blockchain-assisted architecture enabling the owner of a smart car to create an immutable record of every data, called the autobiography of a car, generated within its lifespan. We also explain how the trust about this record is guaranteed by the immutability characteristic of the blockchain. Furthermore, the article describes how the proposed architecture enables a secure and privacy-preserving mechanism for sharing of smart car data among different parties.

In this paper, we provide a review of concepts and developments in operating procedure synthesis (OPS), starting from its early development through to its current state. Operating procedure synthesis is a problem in which a set of equipment manipulations and their orderings must be generated to take the process from an initial state to a goal state. While there has been ongoing research for about 30 years in this area, only a few systems have been reported to be industrially deployed. The approach taken in this paper is, first, to describe the problem in general terms; second, to discuss previous work in this area; and, finally, to present ideas and directions for future work.

This work examines the interplay of inter-personal and inter-organizational trust, two distinct but related concepts, through a theoretic inter-organizational trust-based security model for a multi-agent system information-sharing community. A calculus that mathematically models trust building at the inter-organizational level is at the heart of this model. In inter-organizational or inter-firm exchange, the role of the boundary spanner, an organizational representative, is important in reducing asymmetries that may exist between the two parties. Trust is a crucial component to the dyadic interaction at the inter-personal or boundary spanner level, and the trust established at this level also affects the overall quality of the relationship at the inter-organizational level. Trust, as an aspect of social control, is thus viewed as a more effective mechanism for security in an open, distributed system, like an information-sharing community. The inter-organizational trust-based security model proposed herein represents a soft security approach. It affords several important benefits over traditional hard security mechanisms used in open systems — robustness, scalability, and adaptability. The inter-organizational trust-based model is an important contribution to the computational security community, as other open systems applications of a distributed or pervasive nature could adapt it and realize its benefits. It is also one of a few attempts to model trust building at either the inter-organizational or inter-personal level.

Industrial design processes can be described as human design problem solving, incorporating the acquisition, evaluation, production and transfer of specific knowledge. In this paper, we will describe the connection and interaction between visualization and reasoning during different stages of the design process. Thereby we focus on three early stages of this process: clarifying the task, concepting and designing an overall solution.

This paper provides a rather general description of design processes and more detailed remarks on design knowledge and design actions. It specifically focuses on design concepts as visual key elements in industrial design processes. We will address the importance of externalization and visualization as means for thinking and knowledge generation and transfer in industrial design in general.

The design process is described as an interplay of the parallel and iterative developments of three domains: knowledge, concept and design. In contrast to linear schemes, this paper proposes a design process scheme focusing on iterative circles and parallel processing possibilities. Industrial design knowledge will be described and compared to relevant knowledge in other disciplines, in particular, engineering design knowledge. We will describe the strong link between the designer's individual biographies, design knowledge and the outcome of design processes.

Design concepts will be discussed as extremely compact representations of core characteristics of the artifacts to be designed, serving as a guide to the design process.

Design actions as described in this paper are characterized by the simultaneous occurrence of thought and externalization processes. Different kinds of visualization are discussed in regard of their role in reasoning during industrial design processes.

This paper concludes by sketching two perspectives. One addresses the need for interdisciplinary research on new visualization tools with regard to human reasoning in design processes. The second one gives an impression of how visualization tools and methods of industrial design can supplement other disciplines.

With the rapid growth in the quantity and complexity of scientific knowledge available for scientists, and allied professionals, the problems associated with harnessing this knowledge are well recognized. Some of these problems are a result of the uncertainties and inconsistencies that arise in this knowledge. Other problems arise from heterogeneous and informal formats for this knowledge. To address these problems, developments in the application of knowledge representation and reasoning technologies can allow scientific knowledge to be captured in logic-based formalisms. Using such formalisms, we can undertake reasoning with the uncertainty and inconsistency to allow automated techniques to be used for querying and combining of scientific knowledge. Furthermore, by harnessing background knowledge, the querying and combining tasks can be carried out more intelligently. In this paper, we review some of the significant proposals for formalisms for representing and reasoning with scientific knowledge.

The concept of manipulative abduction is devoted to capture the role of action in many interesting cognitive situations: action provides otherwise unavailable information that enables the agent to solve problems by starting and performing a suitable abductive process of generation or selection of hypotheses. We observe that many external things, usually inert from an epistemological point of view, can be transformed into epistemic mediators. I will present some details derived from the history of the discovery of the non-Euclidean geometries that illustrate the relationships between strategies for anomaly resolution and visual thinking. Geometrical diagrams are external representations that play both a mirror role (to externalize rough mental models) and an unveiling role (as gateways to imaginary entities). I describe them as epistemic mediators able to perform various explanatory, non-explanatory, and instrumental abductive tasks (discovery of new properties or new propositions/hypotheses, provision of suitable sequences of models as able to convincingly verifying theorems, etc.). I am also convinced that they can be exploited and studied in everyday non-mathematical applications also to the aim of promoting new trends in artificial intelligence modeling of various aspects of hypothetical reasoning: finding routes, road signs, buildings maps, for example, in connection with various zooming effects of spatial reasoning. I also think that the cognitive activities of optical, mirror, and unveiling diagrams can be studied in other areas of manipulative and model-based reasoning, such as the ones involving creative, analogical, and spatial inferences, both in science and everyday situations so that this can extend the epistemological, computational, and the psychological theory.

This paper gives an overview of electronic marketplaces which employ agent technology or similar techniques. Special attention is given to negotiation issues. A classification scheme for competitive negotiation depending on the type of the marketplace (business-to-business, business-to-consumer and consumer-to-consumer) and on the range of players (1:1, 1:n and n:m) is introduced. Furthermore, we distinguish between one-issue and multi-issue negotiation, and we consider crisp and fuzzy constraints on either negotiating side. Several existing electronic marketplaces and prototypes of marketplaces are discussed with respect to the classification schema. Our analysis shows that agent-based e-marketplaces are a promising area of e-commerce but they are still far away from real marketplaces. In conclusion we formulate some challenges for further research in the field of multi-agent electronic marketplaces with negotiation between agents.

A multi-agent system architecture for coordination of just-in-time production and distribution is presented. The problem to solve is twofold: first the right amount of resources at the right time should be produced, then these resources should be distributed to the right consumers. In order to solve the first problem, which is hard when the production and/or distribution time is relatively long, each consumer is equipped with an agent that makes predictions of future needs that it sends to a production agent. The second part of the problem is approached by forming clusters of consumers within which it is possible to redistribute resources fast and at a low cost in order to cope with discrepancies between predicted and actual consumption. Redistribution agents are introduced (one for each cluster) to manage the redistribution of resources. The suggested architecture is evaluated in a case study concerning management of district heating systems. Results from a simulation study show that the suggested approach makes it possible to control the trade-off between quality of service and degree of surplus production. We also compare the suggested approach to a reference control scheme (approximately corresponding to the current approach to district heating management), and conclude that it is possible to reduce the amount of resources produced while maintaining the quality of service. Finally, we describe a simulation experiment where the relation between the size of the clusters and the quality of service was studied.

This paper surveys the most representative approaches of knowledge-base revision. After a description of the revision characterization according to the AGM paradigm, the paper reviews different revision methods. In each case, the same example is used, as a reference example, to illustrate the different approaches. Closely connected with revision, some other non-monotonic approaches, like update, are briefly presented.

Hierarchical Task Network (HTN) planning paradigm has been widely used during the last decade to model and solve planning and scheduling (P&S) problems, and it has proved to be very useful in the planning and coordination of human tasks. At the same time, Business Process Management (BPM) tools are being increasingly used in the modeling of organizations’ business practices and processes, but their life cycle has shown to have some shortages (as the possibility to obtain context-dependent plan instances). In this paper we present a methodology and software framework to translate Business Process Models into HTN P&S domains, in order to cover some of these deficiencies.

The basic principle underpinning case-based reasoning (CBR) is that new problems can be solved by reusing solutions to past problems. The generality of this idea means that CBR is finding application in a wide variety of areas. The special advantage of CBR is that a case can be a very convenient means of capturing knowledge, especially in weak theory domains where the relationship between causes and effects may not be well understood. Cases may embody more than problem-solving knowledge; the knowledge in a case may be a creative structure or a complex behavior pattern. The widespread applicability of this idea means that it has been exploited in a diverse range of areas across the arts and sciences. This article provides a brief summary of some of these applications.

As acknowledged by the SESAR (Single European Sky ATM (Air Traffic Management) Research) program, current Air Traffic Control (ATC) systems must be drastically improved to accommodate the predicted traffic growth in Europe. In this context, the Episode 3 project aims at assessing the performance of new ATM concepts, like 4D-trajectory planning and strategic deconfliction.

One of the bottlenecks impeding ATC performances is the hourly capacity constraints defined on each en-route ATC sector to limit the rate of aircraft. Previous works were mainly focused on optimizing the current ground holding slot allocation process devised to satisfy these constraints. We propose to estimate the cost of directly solving all conflicts in the upper airspace with ground holding, provided that aircraft were able to follow their trajectories accurately.

We present a Constraint Programming model of this large-scale combinatorial optimization problem and the results obtained with the FaCiLe (Functional Constraint Library). We study the effect of uncertainties on the departure time and estimate the cost of improving the robustness of our solutions with the Complete Air Traffic Simulator (CATS). Encouraging results were obtained without uncertainty but the costs of robust solutions are prohibitive. Our approach may however be improved, for example, with a prior flight level allocation and the dynamic resolution of remaining conflicts with one of CATS’ modules.

Air traffic management (ATM) under its current paradigm is reaching its structural limits considering the continuously growing demand. The need for a decrease in traffic workload opens numerous problems for optimization, from capacity balancing to conflict solving, using many different degrees of freedom, such as re-routing, flight-level changes, or ground-holding schemes. These problems are usually of a large dimension (there are 30 000 daily flights in Europe in the year 2012) and highly combinatorial, hence challenging for current problem solving technologies. We give brief tutorials on ATM and constraint programming (CP), and survey the literature on deploying CP technology for modelling and solving combinatorial problems that occur in an ATM context.

In this study we present a review of the emerging field of meta-knowledge components as practised over the past decade among a variety of practitioners. We use the artificially defined term “meta-knowledge” to encompass all those different but overlapping notions used by the artificial intelligence and software engineering communities to represent reusable modelling frameworks: ontologies, problem-solving methods, patterns and experience factories and bases, to name but a few. We then elaborate on how meta-knowledge is deployed in the context of system's design to improve its reliability by consistency-checking, enhance its reuse potential and manage its knowledge-sharing. We speculate on its usefulness and explore technologies for supporting deployment of meta-knowledge. We argue that, despite the different approaches being followed in systems design by divergent communities, meta-knowledge is present in all cases, in a tacit or explicit form, and its utilisation depends on pragmatic aspects which we try to identify and critically review on criteria of effectiveness.

The simulation of synthetic humans inhabiting virtual environments is a current research topic with a great number of behavioral problems to be tackled. Semantical virtual environments (SVEs) have recently been proposed not only to ease world modeling but also to enhance the agent–object and agent–agent interaction. Thus, we propose the use of ontologies to define the world’s knowledge base and to introduce semantic levels of detail that help the sensorization of complex scenes—containing lots of interactive objects. The object taxonomy also helps to create general and reusable operativity for autonomous characters—for example, liquids can be poured from containers such as bottles. On the other hand, we use the ontology to define social relations among agents within an artificial society. These relations must be taken into account in order to display socially acceptable decisions. Therefore, we have implemented a market-based social model that reaches coordination and sociability by means of task exchanges. This paper presents a multi-agent framework oriented to simulate socially intelligent characters in SVEs. The framework has been successfully tested in three-dimensional (3D) dynamic scenarios while simulating a virtual university bar, where groups of waiters and customers interact with both the objects in the scene and the other virtual agents, finally displaying complex social behaviors.

Increasing complexity of design in automotive electrical systems has been paralleled by increased demands for analysis of the safety and reliability aspects of those designs. Such demands can place a great burden on the engineers charged with carrying out the analysis. This paper describes how the intended functions of a circuit design can be combined with a qualitative model of the electrical circuit that fulfils the functions, and used to analyse the safety of the design. FLAME, an automated failure mode and effects analysis system based on these techniques, is described in detail. FLAME has been developed over several years, and is capable of composing an FMEA report for many different electrical subsystems. The paper also addresses the issue of how the use of functional and structural reasoning can be extended to sneak circuit analysis and fault tree analysis.