Organic Computing in the Spotlight
Not on the map. Why?
Abstract (arXiv)
Organic Computing is an initiative in the field of systems engineering that proposed to make use of concepts such as self-adaptation and self-organisation to increase the robustness of technical systems. Based on the observation that traditional design and operation concepts reach their limits, transferring more autonomy to the systems themselves should result in a reduction of complexity for users, administrators, and developers. However, there seems to be a need for an updated definition of the term "Organic Computing", of desired properties of technical, organic systems, and the objectives of the Organic Computing initiative. With this article, we will address these points.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Jan 2017.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 2.
4 papers.
- 2021Adaptive Explainable Continual Learning Framework for Regression Problems with Focus on Power Forecastscited by 2
- 2022Active Reinforcement Learning -- A Roadmap Towards Curious Classifier Systems for Self-Adaptationcited by 1
- 2026Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generationcited by 1
- 2026Self-Explainability in Self-Adaptive and Self-Organising Systems: Status and Research Directionscited by 0
- 2026Self-Explainability in Self-Adaptive and Self-Organising Systems: Status and Research Directions8 Jun 2026
- 2026Modernising Reinforcement Learning-Based Navigation for Embodied Semantic Scene Graph Generation26 Mar 2026
- 2022Active Reinforcement Learning -- A Roadmap Towards Curious Classifier Systems for Self-Adaptation11 Jan 2022
- 2021Adaptive Explainable Continual Learning Framework for Regression Problems with Focus on Power Forecasts24 Aug 2021