Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

Klausurtagung des Instituts für Telematik. Schloss Dagstuhl, 29. März bis 1. April 2000

Der vorliegende Bericht gibt einen Überblick über aktuelle Forschungsarbeiten des Instituts für Telematik an der Universität Karlsruhe (TH). Das Institut für Telematik ist in einem Teilgebiet der Informatik tätig, welches durch das Zusammenwachsen von Informatik und Kommunikationstechnik zur Telematik geprägt ist. Es gliedert sich in die Forschungsbereiche Telematik, Telecooperation Office (TecO), Cooperation & Management, Hochleistungsnetze und Netzwerkmanagement sowie dezentrale Systeme und Netzdienste. Die Schwerpunkte des Forschungsbereichs "Telematik" (Prof. Dr. Dr. h.c. mult. G. Krüger) liegen in den Bereichen "Dienstgüte", "Mobilkommunikation" und "Verteilte Systeme". Gemeinsames Ziel ist die Integration heterogener Netze (Festnetze und Funknetze), Rechnersysteme (von Workstations bis zu PDAs) und Softwarekomponenten, um damit den Anwendern eine Vielzahl von integrierten Diensten effizient und mit größtmöglicher Qualität zu erbringen. Das "Telecooperation Office" (TecO, Prof. Dr. Dr. h.c. mult. G. Krüger) ist ein Institutsbereich, der in Zusammenarbeit mit der Industrie anwendungsnahe Forschungsthemen der Telematik aufgreift. Im Mittelpunkt steht die innovative Nutzung von Kommunikationsinfrastrukturen mit den Schwerpunkten Softwaretechnik für Web-Anwendungen, neue Formen der Telekooperation sowie tragbare und allgegenwärtige Technologien (Ubiquitous Computing). Die Kernkompetenz des Forschungsbereichs "Cooperation & Management" (Prof. Dr. S. Abeck) liegt im prozessorientierten Netz-, System- und Anwendungsmanagement. Es werden werkzeuggestützte Managementlösungen für Betriebsprozesse entwickelt und in realen Szenarien erprobt. Ein wichtiges Szenario stellt das multimediale Informationssystem "NEXUS" dar, das als Plattform eines europaweit verteilten Lehr- und Lernsystems genutzt wird. Der Forschungsbereich "Hochleistungsnetze & Netzwerkmanagement" (Prof. Dr. W. Juling) befasst sich mit Technologie und Konzepten moderner leistungsfähiger Netzwerke sowie darüber hinaus mit sämtlichen Aspekten des Managements dieser zumeist ausgedehnten Netze. Um eine enge Abstimmung zwischen Forschungsaktivitäten und betrieblicher Praxis zu erzielen, werden insbesondere auch Synergien zwischen Institut und Rechenzentrum angestrebt. Die Arbeiten des Forschungsbereichs "Dezentrale Systeme und Netzdienste" (Prof. Dr. L. Wolf) befassen sich mit der Unterstützung verteilter Multimedia-Systeme, auch unter Berücksichtigung von Komponenten mit drahtlosem Zugang und den dafür geeigneten Architekturen und Infrastrukturen. Dabei werden vor allem Aspekte der Kommunikationssysteme wie Protokollmechanismen, Ressourcenverwaltung und adaptive und heterogene Systeme untersucht

Design techniques to support aircraft systems development in a collaborative MDO environment

The aircraft design is a complex multidisciplinary and collaborative process. Thousands of disciplinary experts with different design competences are involved within the whole development process. The design disciplines are often in contrast with each other, as their objectives might be not coincident, entailing compromises for the determination of the global optimal solution. Therefore, Multidisciplinary Design and Optimization (MDO) algorithms are being developed to mathematically overcome the divergences among the design disciplines. However, a MDO formulation might identify an optimal solution, but it could be not sufficient to ensure the success of a project. The success of a new project depends on two factors. The first one is relative to the aeronautical product, which has to be compliant with all the capabilities actually demanded by the stakeholders. Furthermore, a “better” airplane may be developed in accordance with customer expectations concerning better performance, lower operating costs and fewer emissions. The second important factor refers to the competitiveness among the new designed product and all the other competitors. The Time-To-Market should be reduced to introduce in the market an innovative product earlier than the other aeronautical industries. Furthermore, development costs should be decreased to maximize profits or to sell the product at a lower price. Finally, the development process must reduce all the risks due to wrong design choices. These two main motivations entail two main objectives of the current dissertation. The first main objective regards the assessment and development of design techniques for the integration of the aircraft subsystems conceptual design discipline within a collaborative and multidisciplinary development methodology. This methodology shall meet all the necessities required to design an optimal and competitive product. The second goal is relative to the employment of the proposed design methodology for the initial development of innovative solutions. As the design process is multidisciplinary, this thesis is focused on the on-board systems discipline, without neglecting the interactions among this discipline with all the other design disciplines. Thus, two kinds of subsystems are treated in the current dissertation. The former deals with hybrid-electric propulsion systems installed aboard Remotely Piloted Aerial Systems (RPASs) and general aviation airplanes. The second case study is centered on More and All Electric on-board system architectures, which are characterized by the removal of the hydraulic and/or pneumatic power generation systems in favor of an enhancement of the electrical system. The proposed design methodology is based on a Systems Engineering approach, according to which all the customer needs and required system functionalities are defined since the earliest phase of the design. The methodology is a five-step process in which several techniques are implemented for the development of a successful product. In Step 1, the design case and the requirements are defined. A Model Based Systems Engineering (MBSE) approach is adopted for the derivation and development of all the functionalities effectively required by all the involved stakeholders. All the design disciplines required in the MDO problem are then collected in Step 2. In particular, all the relations among these disciplines – in terms of inputs/outputs – are outlined, in order to facilitate their connection and the setup of the design workflow. As the present thesis is mainly focused on the on-board system design discipline, several algorithms for the preliminary sizing of conventional and innovative subsystems (included the hybrid propulsion system) are presented. In the third step, an MDO problem is outlined, determining objectives, constraints and design variables. Some design problems are analyzed in the present thesis: un-converged and converged Multidisciplinary Design Analysis (MDA), Design Of Experiments (DOE), optimization. In this regard, a new multi-objective optimization method based on the Fuzzy Logic has been developed during the doctoral research. This proposed process would define the “best” aircraft solution negotiating and relaxing some constraints and requirements characterized by a little worth from the user perspective. In Step 4, the formulation of the MDO problem is then transposed into a MDO framework. Two kinds of design frameworks are here considered. The first one is centered on the subsystems design, with the aim of preliminarily highlighting the impacts of this discipline on the entire Overall Aircraft Design (OAD) process and vice-versa. The second framework is distributed, as many disciplinary experts are involved within the design process. In this case, the level of fidelity of the several disciplinary modules is higher than the first framework, but the effort needed to setup the entire workflow is much higher. The proposed methodology ends with the investigation of the design space through the implemented framework, eventually selecting the solution of the design problem (Step 5). The capability of the proposed methodology and design techniques is demonstrated by means of four application cases. The first case study refers to the initial definition of the physical architecture of a hybrid propulsion system based on a set of needs and capabilities demanded by the customer. The second application study is focused on the preliminary sizing of a hybrid-electric propulsion system to be installed on a retrofit version of a well-known general aviation aircraft. In the third case study, the two kinds of MDO framework previously introduced are employed to design conventional, More Electric and All Electric subsystem architectures for a 90-passenger regional jet. The last case study aims at minimizing the aircraft development costs. A Design-To-Cost approach is adopted for the design of a hybrid propulsion system

Soft computing applied to optimization, computer vision and medicine

Artificial intelligence has permeated almost every area of life in modern society, and its significance continues to grow. As a result, in recent years, Soft Computing has emerged as a powerful set of methodologies that propose innovative and robust solutions to a variety of complex problems. Soft Computing methods, because of their broad range of application, have the potential to significantly improve human living conditions. The motivation for the present research emerged from this background and possibility. This research aims to accomplish two main objectives: On the one hand, it endeavors to bridge the gap between Soft Computing techniques and their application to intricate problems. On the other hand, it explores the hypothetical benefits of Soft Computing methodologies as novel effective tools for such problems. This thesis synthesizes the results of extensive research on Soft Computing methods and their applications to optimization, Computer Vision, and medicine. This work is composed of several individual projects, which employ classical and new optimization algorithms. The manuscript presented here intends to provide an overview of the different aspects of Soft Computing methods in order to enable the reader to reach a global understanding of the field. Therefore, this document is assembled as a monograph that summarizes the outcomes of these projects across 12 chapters. The chapters are structured so that they can be read independently. The key focus of this work is the application and design of Soft Computing approaches for solving problems in the following: Block Matching, Pattern Detection, Thresholding, Corner Detection, Template Matching, Circle Detection, Color Segmentation, Leukocyte Detection, and Breast Thermogram Analysis. One of the outcomes presented in this thesis involves the development of two evolutionary approaches for global optimization. These were tested over complex benchmark datasets and showed promising results, thus opening the debate for future applications. Moreover, the applications for Computer Vision and medicine presented in this work have highlighted the utility of different Soft Computing methodologies in the solution of problems in such subjects. A milestone in this area is the translation of the Computer Vision and medical issues into optimization problems. Additionally, this work also strives to provide tools for combating public health issues by expanding the concepts to automated detection and diagnosis aid for pathologies such as Leukemia and breast cancer. The application of Soft Computing techniques in this field has attracted great interest worldwide due to the exponential growth of these diseases. Lastly, the use of Fuzzy Logic, Artificial Neural Networks, and Expert Systems in many everyday domestic appliances, such as washing machines, cookers, and refrigerators is now a reality. Many other industrial and commercial applications of Soft Computing have also been integrated into everyday use, and this is expected to increase within the next decade. Therefore, the research conducted here contributes an important piece for expanding these developments. The applications presented in this work are intended to serve as technological tools that can then be used in the development of new devices

Networking and application interface technology for wireless sensor network surveillance and monitoring

Distributed unattended ground sensor (UGS) networks are commonly deployed to support wide area battlefield surveillance and monitoring missions. The information they generate has proven to be valuable in providing a necessary tactical information advantage for command and control, intelligence and reconnaissance field planning. Until recently, however, there has been greater emphasis within the defence research community for UGS networks to fulfil their mission objectives successfully, with minimal user interaction. For a distributed UGS scenario, this implies a network centric capability, where deployed UGS networks can self-manage their behaviour in response to dynamic environmental changes. In this thesis, we consider both the application interface and networking technologies required to achieve a network centric capability, within a distributed UGS surveillance setting. Three main areas of work are addressed towards achieving this. The first area of work focuses on a capability to support autonomous UGS network management for distributed surveillance operations. The network management aspect is framed in terms of how distributed sensors can collaborate to achieve their common mission objectives and at the same time, conserve their limited network resources. A situation awareness methodology is used, in order to enable sensors which have similar understanding towards a common objective to be utilised, for collaboration and to allow sensor resources to be managed as a direct relationship according to, the dynamics of a monitored threat. The second area of work focuses on the use of geographic routing to support distributed surveillance operations. Here we envisage the joint operation of unmanned air vehicles and UGS networks, working together to verify airborne threat observations. Aerial observations made in this way are typically restricted to a specific identified geographic area. Information queries sent to inquire about these observations can also be routed and restricted to using this geographic information. In this section, we present our bio-inspired geographic routing strategy, with an integrated topology control function to facilitate this. The third area of work focuses on channel aware packet forwarding. Distributed UGS networks typically operate in wireless environments, which can be unreliable for packet forwarding purposes. In this section, we develop a capability for UGS nodes to decide which packet forwarding links are reliable, in order to reduce packet transmission failures and improve overall distributed networking performance

Uncertainty analysis in competitive bidding for service contracts

Sustainable production and consumption have become more important internationally, which has led to the transformation of market structures and competitive situations into the direction of servitisation. This means that manufacturing companies are forced to compete through the supply of services as opposed to products. Particularly the suppliers of long-life products such as submarines and airplanes no longer simply sell these products but provide their capability or availability. Companies such as Rolls-Royce Engines achieve 60% of their revenue through selling a service rather than the engine itself. For a manufacturing company, the shift towards being a service provider means that they usually have to bid for service contracts, sometimes competitively. In the context of competitive bidding, the decision makers face various uncertainties that influence their decision. Ignoring these uncertainties or their influences can result in problems such as the generation of too little profit or even a loss or the exposure to financial risks. Raising the decision maker’s awareness of the uncertainties in the form of e.g. a decision matrix, expressing the trade-off between the probability of winning the contract and the probability of making a profit, aims at integrating these factors in the decision process. The outcome is to enable the bidding company to make a more informed decision. This was the focus of the research presented in this thesis. The aim of this research was to support the pricing decision by defining a process for modelling the influencing uncertainties and including them in a decision matrix depicting the trade-off between the probability of winning the contract and the probability of making a profit. Three empirical studies are described and the associated decision process and influencing uncertainties are discussed. Based on these studies, a conceptual framework was defined which depicts the influencing factors on a pricing decision at the bidding stage and the uncertainties within these. The framework was validated with a case study in contract bidding where the uncertainties were modelled and included in a decision matrix depicting the probability of winning the contract and the probability of making a profit. The main contributions of this research are the identification of the uncertainties influencing a pricing decision, the depiction of these in a conceptual framework, a method for ascertaining how to model these uncertainties and assessing the use of such an approach via an industrial case study.EThOS - Electronic Theses Online ServiceGBUnited Kingdo