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• W2612081826 abstract "This paper is a summary of the plenary presentation. The objectives of the presentation are threefold: a) to discuss conceptual foundations of cognitive computing, b) to demonstrate their impact on intelligent systems design, and c) to present a brief summary of relevant project experiences. An introduction to knowledgebased and cognitive systems, and the explanation of their origins and principles are given. Then, an agent metaphor is introduced as the basis for design of high autonomy, cognitive architectures. Examples of projects from both industry and research laboratories that leverage from the above concepts are discussed. Some recent work that focuses on decision making in complex, information rich environments, multi-agent gaming models, and implementation of symbolic representation techniques in highly flexible, reusable, object-oriented visualization systems is presented. INTRODUCTION AND MOTIVATION Cognitive computing is an emerging approach that builds upon a wealth of research and development work in Artificial Intelligence (AI). It strives to provide methods to construct and operate systems that “know what they are doing” (Brachman 2002). From a perspective of practicing modelers and systems engineers, the primary motivation behind adopting cognitive methods is to better support the design and deployment of complex, intelligent systems. It is also the systems’ complexity that motivates us strongly to develop new integration techniques that help achieve high levels of autonomy and intelligence. As modelers and designers, we are excellent at constructing system modules and subcomponents. However, we often falter at the integration of those components not just in a structural, but also in a functional sense. For several years now, the Defense Advanced Research Projects Agency (DARPA) has been driving an effort to build systems that are able to acquire and accumulate knowledge, reason, learn, explain themselves, and be aware of their own behavior (and be robust). Clearly, these are very highly sophisticated objectives and, realistically, there is currently no artificial system that can exhibit that kind of a complex, integrative behavior. From an engineering perspective, computer-aided support at the higher design level is urgently needed. Whereas excellent support exists at lower design levels — for instance, in circuit, or VLSI design — support for integrating hardware and software components at higher system levels is poor. Thus, our desire is to develop adequate modeling tools that support the development of complex heterogeneous systems, allow for reuse of models and modules, and help us in rapid prototyping. In the following sections, we examine how the cognitive techniques could help us accomplish those goals. We begin with a discussion of cognitive systems and their underlying AI paradigms." @default.
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• W2612081826 title "Cognitive computing: Principles, architectures, and applications" @default.
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