By Andreas Tolk
This quantity includes a range of cutting-edge contributions to themes facing complicated structures within the Knowledge-based atmosphere. advanced structures are ubiquitous. Examples contain, yet will not be restricted to method of platforms, Service-oriented ways, Agent-based structures, and complicated disbursed digital platforms. most of these are program domain names that require wisdom, engineering, and administration equipment past the scope of conventional platforms. The chapters during this booklet care for a variety of proper themes, starting from uncertainty illustration and administration to using ontological potential in help of large-scale company integration.
All contributions have been invited in line with the targeted attractiveness of the contributing authors of their box in the course of workshops and symposia. by way of bringing these types of various elements jointly in a single quantity, our purpose used to be first to offer various instruments to the reader in aid of his reviews and paintings, and moment to teach how the various features awarded within the chapters are complementary contributing in the direction of an rising self-discipline to deal with advanced platforms. the typical denominator of all chapters is using knowledge-based equipment, specifically ontological skill. The chapters are labeled into idea contributions and functional applications.
We desire that this quantity might help researchers, scholars, and practitioners in dealing with the demanding situations of integration, operation, and evaluate of complicated systems.
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Additional info for Complex Systems in Knowledge-based Environments: Theory, Models and Applications
Fig. 17. SSBNs for the Parameter Learning Example 2 Uncertainty Representation and Reasoning in Complex Systems 33 It may seem cumbersome to define different random variables, StarshipLengthInd and StarshipLengthDep, for each hypothesis about the influences on a starship’s length. As the number of structural hypotheses becomes large, this can become quite unwieldy. Fortunately, we can circumvent this difficulty by introducing a typed version of MEBN and allowing the distributions of random variables to depend on the type of their argument.
However, M&S applications best exhibit the challenges that have to be met when evaluating and managing interoperation and composability tasks in complex systems. The reason is that M&S applications make explicit the various layers of abstraction that are often hidden in other system domains: the conceptualization layer leading to the model, the implementation layer leading to the simulation, and technical questions of the underlying network. Each layer is tightly connected with different aspects of interoperation.
System modeling and architecture approaches, such as summarized in (Buede 1999) and other system engineering books show that a good system architecture is based on a rigid analysis of the underlying requirements, which leads to a conceptualization of necessary actors and processes. This conceptualization drives the architectural artifacts, which are used to build the system based on the available technology. It 3 A Layered Approach to Composition and Interoperation in Complex Systems 43 is also good practice to separate business and application logic from underlying technology.
Complex Systems in Knowledge-based Environments: Theory, Models and Applications by Andreas Tolk
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