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Documents authored by Würtz, Rolf P.

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Würtz, Rolf P.

Document
DOI: 10.4230/DagSemProc.06031.1
06031 Abstracts Collection – Organic Computing – Controlled Emergence

Authors: Kirstie Bellman, Peter Hofmann, Christian Müller-Schloer, Hartmut Schmeck, and Rolf P. Würtz

Published in: Dagstuhl Seminar Proceedings, Volume 6031, Organic Computing - Controlled Emergence (2006)

Abstract
Organic Computing has emerged recently as a challenging vision for future information processing systems, based on the insight that we will soon be surrounded by large collections of autonomous systems equipped with sensors and actuators to be aware of their environment, to communicate freely, and to organize themselves in order to perform the actions and services required. Organic Computing Systems will adapt dynamically to the current conditions of its environment, they will be self-organizing, self-configuring, self-healing, self-protecting, self-explaining, and context-aware. From 15.01.06 to 20.01.06, the Dagstuhl Seminar 06031 ``Organic Computing – Controlled Emergence'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. The seminar was characterized by the very constructive search for common ground between engineering and natural sciences, between informatics on the one hand and biology, neuroscience, and chemistry on the other. The common denominator was the objective to build practically usable self-organizing and emergent systems or their components. An indicator for the practical orientation of the seminar was the large number of OC application systems, envisioned or already under implementation, such as the Internet, robotics, wireless sensor networks, traffic control, computer vision, organic systems on chip, an adaptive and self-organizing room with intelligent sensors or reconfigurable guiding systems for smart office buildings. The application orientation was also apparent by the large number of methods and tools presented during the seminar, which might be used as building blocks for OC systems, such as an evolutionary design methodology, OC architectures, especially several implementations of observer/controller structures, measures and measurement tools for emergence and complexity, assertion-based methods to control self-organization, wrappings, a software methodology to build reflective systems, and components for OC middleware. Organic Computing is clearly oriented towards applications but is augmented at the same time by more theoretical bio-inspired and nature-inspired work, such as chemical computing, theory of complex systems and non-linear dynamics, control mechanisms in insect swarms, homeostatic mechanisms in the brain, a quantitative approach to robustness, abstraction and instantiation as a central metaphor for understanding complex systems. Compared to its beginnings, Organic Computing is coming of age. The OC vision is increasingly padded with meaningful applications and usable tools, but the path towards full OC systems is still complex. There is progress in a more scientific understanding of emergent processes. In the future, we must understand more clearly how to open the configuration space of technical systems for on-line modification. Finally, we must make sure that the human user remains in full control while allowing the systems to optimize.
Cite as

Kirstie Bellman, Peter Hofmann, Christian Müller-Schloer, Hartmut Schmeck, and Rolf P. Würtz. 06031 Abstracts Collection – Organic Computing – Controlled Emergence. In Organic Computing - Controlled Emergence. Dagstuhl Seminar Proceedings, Volume 6031, pp. 1-19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{bellman_et_al:DagSemProc.06031.1,
  author =	{Bellman, Kirstie and Hofmann, Peter and M\"{u}ller-Schloer, Christian and Schmeck, Hartmut and W\"{u}rtz, Rolf P.},
  title =	{{06031 Abstracts Collection – Organic Computing – Controlled Emergence}},
  booktitle =	{Organic Computing - Controlled Emergence},
  pages =	{1--19},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6031},
  editor =	{Kirstie Bellman and Peter Hofmann and Christian M\"{u}ller-Schloer and Hartmut Schmeck and Rolf W\"{u}rtz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06031.1},
  URN =		{urn:nbn:de:0030-drops-5777},
  doi =		{10.4230/DagSemProc.06031.1},
  annote =	{Keywords: Emergence, self-organization, self-configuration, self-healing, self-protection, self-explaining, context-awareness}
}
Document
DOI: 10.4230/DagSemProc.06031.2
06031 Executive Summary – Organic Computing – Controlled Emergence

Authors: Kirstie Bellman, Peter Hofmann, Christian Müller-Schloer, Hartmut Schmeck, and Rolf P. Würtz

Published in: Dagstuhl Seminar Proceedings, Volume 6031, Organic Computing - Controlled Emergence (2006)

Abstract
Organic Computing has emerged recently as a challenging vision for future information processing systems, based on the insight that we will soon be surrounded by systems with massive numbers of processing elements, sensors and actuators, many of which will be autonomous. Because of the size of these systems it is infeasible for us to monitor and control them entirely from external observations; instead they will need to help us monitor, control and adapt themselves. To do so, these components will need to be aware of their environment, to communicate freely, and to organize themselves in order to perform the actions and services that are required. The presence of networks of intelligent systems in our environment opens up fascinating application areas but, at the same time, bears the problem of their controllability. Hence, we have to construct these systems which we increasingly depend on as robust, safe, flexible, and trustworthy as possible. In particular, a strong orientation towards human needs as opposed to a pure implementation of the technologically possible seems absolutely central. In order to achieve these goals, our technical systems will have to act more independently, flexibly, and autonomously, i.e., they will have to exhibit lifelike properties. We call those systems ''organic''. Hence, an ''Organic Computing System'' is a technical system which adapts dynamically to the current conditions of its environment. It will be selforganizing, selfconfiguring, selfhealing, selfprotecting, selfexplaining, and context-aware.
Cite as

Kirstie Bellman, Peter Hofmann, Christian Müller-Schloer, Hartmut Schmeck, and Rolf P. Würtz. 06031 Executive Summary – Organic Computing – Controlled Emergence. In Organic Computing - Controlled Emergence. Dagstuhl Seminar Proceedings, Volume 6031, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{bellman_et_al:DagSemProc.06031.2,
  author =	{Bellman, Kirstie and Hofmann, Peter and M\"{u}ller-Schloer, Christian and Schmeck, Hartmut and W\"{u}rtz, Rolf P.},
  title =	{{06031 Executive Summary – Organic Computing – Controlled Emergence}},
  booktitle =	{Organic Computing - Controlled Emergence},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6031},
  editor =	{Kirstie Bellman and Peter Hofmann and Christian M\"{u}ller-Schloer and Hartmut Schmeck and Rolf W\"{u}rtz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06031.2},
  URN =		{urn:nbn:de:0030-drops-5788},
  doi =		{10.4230/DagSemProc.06031.2},
  annote =	{Keywords: Emergence, self-organization, self-configuration, self-healing, self-protection, self-explaining, context-awareness}
}
Document
DOI: 10.4230/DagSemProc.06031.5
Feature-driven Emergence of Model Graphs for Object Recognition and Categorization

Authors: Günter Westphal, Christoph von der Malsburg, and Rolf P. Würtz

Published in: Dagstuhl Seminar Proceedings, Volume 6031, Organic Computing - Controlled Emergence (2006)

Abstract
An important requirement for the expression of cognitive structures is the ability to form mental objects by rapidly binding together constituent parts. In this sense, one may conceive the brain's data structure to have the form of graphs whose nodes are labeled with elementary features. These provide a versatile data format with the additional ability to render the structure of any mental object. Because of the multitude of possible object variations the graphs are required to be dynamic. Upon presentation of an image a so-called model graph should rapidly emerge by binding together memorized subgraphs derived from earlier learning examples driven by the image features. In this model, the richness and flexibility of the mind is made possible by a combinatorical game of immense complexity. Consequently, the emergence of model graphs is a laborious task which, in computer vision, has most often been disregarded in favor of employing model graphs tailored to specific object categories like, for instance, faces in frontal pose. Recognition or categorization of arbitrary objects, however, demands dynamic graphs. In this work we propose a form of graph dynamics, which proceeds in two steps. In the first step component classifiers, which decide whether a feature is present in an image, are learned from training images. For processing arbitrary objects, features are small localized grid graphs, so-called parquet graphs, whose nodes are attributed with Gabor amplitudes. Through combination of these classifiers into a linear discriminant that conforms to Linsker's infomax principle a weighted majority voting scheme is implemented. It allows for preselection of salient learning examples, so-called model candidates, and likewise for preselection of categories the object in the presented image supposably belongs to. Each model candidate is verified in a second step using a variant of elastic graph matching, a standard correspondence-based technique for face and object recognition. To further differentiate between model candidates with similar features it is asserted that the features be in similar spatial arrangement for the model to be selected. Model graphs are constructed dynamically by assembling model features into larger graphs according to their spatial arrangement. From the viewpoint of pattern recognition, the presented technique is a combination of a discriminative (feature-based) and a generative (correspondence-based) classifier while the majority voting scheme implemented in the feature-based part is an extension of existing multiple feature subset methods. We report the results of experiments on standard databases for object recognition and categorization. The method achieved high recognition rates on identity, object category, pose, and illumination type. Unlike many other models the presented technique can also cope with varying background, multiple objects, and partial occlusion.
Cite as

Günter Westphal, Christoph von der Malsburg, and Rolf P. Würtz. Feature-driven Emergence of Model Graphs for Object Recognition and Categorization. In Organic Computing - Controlled Emergence. Dagstuhl Seminar Proceedings, Volume 6031, pp. 1-46, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{westphal_et_al:DagSemProc.06031.5,
  author =	{Westphal, G\"{u}nter and von der Malsburg, Christoph and W\"{u}rtz, Rolf P.},
  title =	{{Feature-driven Emergence of Model Graphs for Object Recognition and Categorization}},
  booktitle =	{Organic Computing - Controlled Emergence},
  pages =	{1--46},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{6031},
  editor =	{Kirstie Bellman and Peter Hofmann and Christian M\"{u}ller-Schloer and Hartmut Schmeck and Rolf W\"{u}rtz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.06031.5},
  URN =		{urn:nbn:de:0030-drops-5756},
  doi =		{10.4230/DagSemProc.06031.5},
  annote =	{Keywords: Graph matching, recognition, categorization, computer vision, self-organization, emergence}
}

Würtz, Rolf

Document
DOI: 10.4230/DagSemProc.08141.1
08141 Abstracts Collection – Organic Computing - Controlled Self-organization

Authors: Kirstie Bellman, Mike Hinchey, Christian Müller-Schloer, Hartmut Schmeck, and Rolf Würtz

Published in: Dagstuhl Seminar Proceedings, Volume 8141, Organic Computing - Controlled Self-organization (2008)

Abstract
From March 30th to April 4th 2008, the Dagstuhl Seminar 08141 "Organic Computing - Controlled Self-organization"' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available.
Cite as

Kirstie Bellman, Mike Hinchey, Christian Müller-Schloer, Hartmut Schmeck, and Rolf Würtz. 08141 Abstracts Collection – Organic Computing - Controlled Self-organization. In Organic Computing - Controlled Self-organization. Dagstuhl Seminar Proceedings, Volume 8141, pp. 1-17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{bellman_et_al:DagSemProc.08141.1,
  author =	{Bellman, Kirstie and Hinchey, Mike and M\"{u}ller-Schloer, Christian and Schmeck, Hartmut and W\"{u}rtz, Rolf},
  title =	{{08141 Abstracts Collection – Organic Computing - Controlled Self-organization}},
  booktitle =	{Organic Computing - Controlled Self-organization},
  pages =	{1--17},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8141},
  editor =	{Kirstie Bellman and Michael G. Hinchey and Christian M\"{u}ller-Schloer and Hartmut Schmeck and Rolf W\"{u}rtz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08141.1},
  URN =		{urn:nbn:de:0030-drops-15675},
  doi =		{10.4230/DagSemProc.08141.1},
  annote =	{Keywords: Organic computing, self-organisation, design, adaptivity}
}
Document
DOI: 10.4230/DagSemProc.08141.2
08141 Executive Summary – Organic Computing - Controlled Self-organization

Authors: Kirstie Bellman, Mike Hinchey, Christian Müller-Schloer, Hartmut Schmeck, and Rolf Würtz

Published in: Dagstuhl Seminar Proceedings, Volume 8141, Organic Computing - Controlled Self-organization (2008)

Abstract
Organic Computing (OC) has become a challenging vision for the design of future information processing systems: As they become increasingly powerful, cheaper and smaller, our environment will be filled with collections of autonomous systems equipped with sensors and actuators to be aware of their environment, to communicate, and to organize themselves in order to perform the actions and servic-es that seem to be required. However, due to increasing complexity we will not be able to explicitly design and manage all intelligent components of a digitally enhanced environment in every detail and anticipate every possible configuration. Therefore, our technical systems will have to act more independently, flexibly, and autonomously, i.e., they will have to exhibit life-like properties. We call such systems "organic". Hence, an "Organic Computing System" is a technical system, which adapts dynamically to the current conditions of its environment. It will be self-organizing, self-configuring, self-healing, self-protecting, self-explaining, and context-aware.
Cite as

Kirstie Bellman, Mike Hinchey, Christian Müller-Schloer, Hartmut Schmeck, and Rolf Würtz. 08141 Executive Summary – Organic Computing - Controlled Self-organization. In Organic Computing - Controlled Self-organization. Dagstuhl Seminar Proceedings, Volume 8141, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2008)

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@InProceedings{bellman_et_al:DagSemProc.08141.2,
  author =	{Bellman, Kirstie and Hinchey, Mike and M\"{u}ller-Schloer, Christian and Schmeck, Hartmut and W\"{u}rtz, Rolf},
  title =	{{08141 Executive Summary – Organic Computing - Controlled Self-organization}},
  booktitle =	{Organic Computing - Controlled Self-organization},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8141},
  editor =	{Kirstie Bellman and Michael G. Hinchey and Christian M\"{u}ller-Schloer and Hartmut Schmeck and Rolf W\"{u}rtz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08141.2},
  URN =		{urn:nbn:de:0030-drops-15660},
  doi =		{10.4230/DagSemProc.08141.2},
  annote =	{Keywords: Organic Computing}
}
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