Understanding Error Correction and its Role as Part of the Communication Channel in Environments composed of Self-Integrating Systems

The raise of complexity of technical systems also raises knowledge required to set them up and to maintain them. The cost to evolve such systems can be prohibitive. In the field of Autonomic Computing, technical systems should therefore have various self-healing capabilities allowing system owners to provide only partial, potentially inconsistent updates of the system. The self-healing or self-integrating system shall find out the remaining changes to communications and functionalities in order to accommodate change and yet still restore function. This issue becomes even more interesting in context of Internet of Things and Industrial Internet where previously unexpected device combinations can be assembled in order to provide a surprising new function. In order to pursue higher levels of self-integration capabilities I propose to think of self-integration as sophisticated error correcting communications. Therefore, this paper discusses an extended scope of error correction with the purpose to emphasize error correction's role as an integrated element of bi-directional communication channels in self-integrating, autonomic communication scenarios.

Exploring high-level Perspectives on Self-Configuration Capabilities of Systems

Optimization of product performance repetitively introduces the need to make products adaptive in a more general sense. This more general idea is often captured under the term 'self-configuration'. Despite the importance of such capability, research work on this feature appears isolated by technical domains. It is not easy to tell quickly whether the approaches chosen in different technological domains introduce new ideas or whether the differences just reflect domain idiosyncrasies. For the sake of easy identification of key differences between systems with self-configuring capabilities, I will explore higher level concepts for understanding self-configuration, such as the {\Omega}-units, in order to provide theoretical instruments for connecting different areas of technology and research.

Efficient Estimation of k for the Nearest Neighbors Class of Methods

The k Nearest Neighbors (kNN) method has received much attention in the past decades, where some theoretical bounds on its performance were identified and where practical optimizations were proposed for making it work fairly well in high dimensional spaces and on large datasets. From countless experiments of the past it became widely accepted that the value of k has a significant impact on the performance of this method. However, the efficient optimization of this parameter has not received so much attention in literature. Today, the most common approach is to cross-validate or bootstrap this value for all values in question. This approach forces distances to be recomputed many times, even if efficient methods are used. Hence, estimating the optimal k can become expensive even on modern systems. Frequently, this circumstance leads to a sparse manual search of k. In this paper we want to point out that a systematic and thorough estimation of the parameter k can be performed efficiently. The discussed approach relies on large matrices, but we want to argue, that in practice a higher space complexity is often much less of a problem than repetitive distance computations.

How to avoid ethically relevant Machine Consciousness

This paper discusses the root cause of systems perceiving the self experience and how to exploit adaptive and learning features without introducing ethically problematic system properties.

Differences between Industrial Models of Autonomy and Systemic Models of Autonomy

This paper discusses the idea of levels of autonomy of systems - be this technical or organic - and compares the insights with models employed by industries used to describe maturity and capability of their products.