Autor: Rolf Drechsler

Optimisation is an essential task in many situations. The class of evolutionary algorithms is a population-based, heuristic technique for optimisation. They allow the optimisation of multi-modal problems even with distorted search spaces. They can propose several solutions instead of just one. An important aspect of evolutionary algorithms is encoding search space candidates. In the optimisation of processes, this is a non-trivial task. This article describes a successfully tested encoding.

To infer human intentions by approaches, which are embedded into technical systems, is the foundation of a future key technology that enables the development of novel assistive devices. These devices provide solutions to current and future challenges that are caused by the demographic change and requirements of  “Industry 4.0”. Embedded Brain Reading enables a mobile recognition of human intention embedded into a technical system to support users fault tolerantly. The model of the approach suggests that man-machine interaction is verifiable for correctness and completeness for its safe usage.

To manage the increasing complexity in current hardware design processes, current systems are increasingly designed on abstract layers. While the more rapid development of prototypes is a clear advantage of this paradigm, these designs suffer from being closed up and hard to analyze. There is no simple way to extract a system’s structure from its description anymore. Nevertheless, the designers should get all the information they need during development. The computer is assisting in this process with the observation of its inner self: The simulated hardware is supervised by an artificial intelligence (AI). It learns about a system’s functions while the system itself is running. Dependencies and connections inside this system are retrieved independent from their availability, thus speeding up the development process.

The design of complex systems usually starts with a natural language specification which serves as the basis for the ongoing implementation. To deal with the increasing complexity, these informal specifications are extended by means of formal modeling languages such as the Unified Modeling Language (UML) and the Object Constraint Language (OCL). They enable to check the specification for conceptual errors and inconsistencies before a precise implementation is available. This paper presents methods which make use of these possibilities. It is illustrated which errors can already exist in specifications and how they can be detected automatically.