Remarks on Self-organization and Trust in Organic Computing Systems

Adaptivity and self-organization in organic computing systems

ACM Transactions on Autonomous and Adaptive Systems ◽

10.1145/1837909.1837911 ◽

2010 ◽

Vol 5 (3) ◽

pp. 1-32 ◽

Cited By ~ 44

Author(s):

Hartmut Schmeck ◽

Christian Müller-Schloer ◽

Emre Çakar ◽

Moez Mnif ◽

Urban Richter

Keyword(s):

Self Organization ◽

Computing Systems ◽

Organic Computing

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A Universal Self-Organization Mechanism for Role-Based Organic Computing Systems

Lecture Notes in Computer Science - Autonomic and Trusted Computing ◽

10.1007/978-3-642-02704-8_3 ◽

2009 ◽

pp. 17-31 ◽

Cited By ~ 15

Author(s):

Florian Nafz ◽

Frank Ortmeier ◽

Hella Seebach ◽

Jan-Philipp Steghöfer ◽

Wolfgang Reif

Keyword(s):

Self Organization ◽

Computing Systems ◽

Role Based ◽

Organic Computing ◽

Organization Mechanism

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Design and construction of organic computing systems

2007 IEEE Congress on Evolutionary Computation ◽

10.1109/cec.2007.4425021 ◽

2007 ◽

Cited By ~ 15

Author(s):

Hella Seebach ◽

Frank Ortmeier ◽

Wolfgang Reif

Keyword(s):

Computing Systems ◽

Organic Computing ◽

Design And Construction

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Self-Conscious Modeling (Modellierung bewusster Systeme)

it - Information Technology ◽

10.1524/itit.2005.47.4.188 ◽

2005 ◽

Vol 47 (4) ◽

Author(s):

Kirstie L. Bellman

Keyword(s):

Computing Systems ◽

Computer Based ◽

Generative Processes ◽

And Control ◽

Reflective Systems ◽

Complex Computer ◽

Organic Computing ◽

Monitor And Control

SummuryIncreasingly diverse and complex computer-based support underlies critical human processes, such as education, commerce, medicine, science, defense, and government. These systems are fed massive amounts of data and due to the complexity and size of these systems, they are integrating and interfacing with each other with less human oversight. Soon, they will need to build, refine, and elaborate their own models and processes, making more decisions about what information to use in what manner and how to approach problems or goals. Hence, these systems must be able to reason about and report out to us their modeling and processing choices in order to help us monitor and control their operations and interactions. In this paper, we discuss our work on creating reflective systems, and how reflection coupled with “generative processes” and “cognitive instrumentation” will help enable organic computing systems. We then briefly describe our testbed for studying self-conscious modeling.

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Thermodynamic Computing: An Intellectual and Technological Frontier

Proceedings ◽

10.3390/proceedings2020047023 ◽

2020 ◽

Vol 47 (1) ◽

pp. 23

Author(s):

Todd Hylton

Keyword(s):

Machine Learning ◽

Device Fabrication ◽

Power Supplies ◽

Self Organization ◽

Technological Systems ◽

Computing Systems ◽

Cooling Systems ◽

Computing Paradigm ◽

Transport Losses ◽

State Changes

Concepts from thermodynamics are ubiquitous in computing systems today—e.g., in power supplies and cooling systems, in signal transport losses, in device fabrication, in state changes, and in the methods of machine learning. Here we propose that thermodynamics should be the central, unifying concept in future computing systems. In particular, we suppose that future computing technologies will thermodynamically evolve in response to electrical and information potential in their environment and, therefore, address the central challenges of energy efficiency and self-organization in technological systems. In this article, we summarize the motivation for a new computing paradigm grounded in thermodynamics and articulate a vision for such future systems.

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