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In this thesis it is posed that the central object of preference discovery is a co-creative process in which the Other can be represented by a machine. It explores efficient methods to enhance introverted intuition using extraverted intuition's communication lines. Possible implementations of such processes are presented using novel algorithms that perform divergent search to feed the users' intuition with many examples of high quality solutions, allowing them to take influence interactively. The machine feeds and reflects upon human intuition, combining both what is possible and preferred. The machine model and the divergent optimization algorithms are the motor behind this co-creative process, in which machine and users co-create and interactively choose branches of an ad hoc hierarchical decomposition of the solution space.
The proposed co-creative process consists of several elements: a formal model for interactive co-creative processes, evolutionary divergent search, diversity and similarity, data-driven methods to discover diversity, limitations of artificial creative agents, matters of efficiency in behavioral and morphological modeling, visualization, a connection to prototype theory, and methods to allow users to influence artificial creative agents. This thesis helps putting the human back into the design loop in generative AI and optimization.
The encoding of solutions in black-box optimization is a delicate, handcrafted balance between expressiveness and domain knowledge between exploring a wide variety of solutions, and ensuring that those solutions are useful. Our main insight is that this process can be automated by generating a dataset of high-performing solutions with a quality diversity algorithm (here, MAP-Elites), then learning a representation with a generative model (here, a Varia-tional Autoencoder) from that dataset. Our second insight is that this representation can be used to scale quality diversity optimization to higher dimensions-but only if we carefully mix solutions generated with the learned representation and those generated with traditional variation operators. We demonstrate these capabilities by learning an low-dimensional encoding for the inverse kinemat-ics of a thousand joint planar arm. The results show that learned representations make it possible to solve high-dimensional problems with orders of magnitude fewer evaluations than the standard MAP-Elites, and that, once solved, the produced encoding can be used for rapid optimization of novel, but similar, tasks. The presented techniques not only scale up quality diversity algorithms to high dimensions, but show that black-box optimization encodings can be automatically learned, rather than hand designed.
The small and remote households in Northern regions demand thermal energy rather than electricity. Wind turbine in such places can be used to convert wind energy into thermal energy directly using a heat generator based on the principle of the Joule machine. The heat generator driven by a wind turbine can reduce the cost of energy for heating system. However the optimal performance of the system depends on the torque-speed characteristics of the wind turbine and the heat generator. To achieve maximum efficiency of operation both characteristics should be matched. In the article the condition of optimal performance is developed and an example of the system operating at maximum efficiency is simulated.
The Render Cache [1,2] allows the interactive display of very large scenes, rendered with complex global illumination models, by decoupling camera movement from the costly scene sampling process. In this paper, the distributed execution of the individual components of the Render Cache on a PC cluster is shown to be a viable alternative to the shared memory implementation.As the processing power of an entire node can be dedicated to a single component, more advanced algorithms may be examined. Modular functional units also lead to increased flexibility, useful in research as well as industrial applications.We introduce a new strategy for view-driven scene sampling, as well as support for multiple camera viewpoints generated from the same cache. Stereo display and a CAVE multi-camera setup have been implemented.The use of the highly portable and inter-operable CORBA networking API simplifies the integration of most existing pixel-based renderers. So far, three renderers (C++ and Java) have been adapted to function within our framework.
Digitaltechnik
(2022)
Moderne Digitaltechnik, umfassend und kompakt: Dieses Lehr- und Übungsbuch spannt den Bogen von den Grundlagen der Digitaltechnik über den Entwurf mit VHDL und Komponenten digitaler Systeme bis zu modernen Mikrocontrollern der STM32-Serie.
Die 8. Auflage wurde aktualisiert und die Themenbereiche Mikroprozessoren und Mikrocontroller grundlegend überarbeitet.
Digitaltechnik
(2016)
Technische Innovationen verändern den Alltag enorm – auch den von Journalisten. Technik-Fachjournalisten sind daher gefragt wie nie. Was sie können müssen, wie in den Medien über Digitalisierung berichtet wird und inwiefern künstliche Intelligenz (KI) Journalisten in Zukunft überflüssig machen wird, beantwortet der Medienwissenschaftler Andreas Schümchen im Gespräch mit dem "Fachjournalist".