1. Nature-inspired Robustness Rüdiger W. Brause

2. Robustness, NOT evolvability or stability for
Introduction
Robustness, NOT evolvability or stability
for
disturbances in ecosystems
cell response to environmental or genetic change
computer performance at input errors, disk failures, network overload
resilience of a political institution during societal flux
viability of a technological product in wildly changing markets
Robustness = aspect of structural stability
NiSIS Workshop, Mallorca R.Brause: Nature-inspired Robustness

3. Open Questions
robustness of ecosystems
What are the organizational principles (possibilities include spatial structure, redundancy, modularity, diversification, and hierarchy among others) that characterize highly robust entities?
Why do they change after long periods of stability, e.g. the society of the former soviet union?
How do non-robust ecosystems look like and how they evolve?
 Only the most robust interaction networks will survive and build the core of the social network.
NiSIS Workshop, Mallorca R.Brause: Nature-inspired Robustness

4. robustness of computer systems
Open Questions
robustness of computer systems
All VLSI chips are subject to variations due to the fabrication process (affine arithmetics). Structural robustness?
self-healing, self-configurating computers (organic computing) How ?
NiSIS Workshop, Mallorca R.Brause: Nature-inspired Robustness

5. Modelling, e.g. modelling of biochemical pathways
Open Questions
Modelling, e.g. modelling of biochemical pathways
Traditional time dynamic modeling
fuzzy clustering stage
dynamical interaction of the clusters by linear differential equations based on the expression data of selected genes
selection criterion: most simple network
But: after long evolutionary development, small genetic mutations will not cause fatal changes any more.
NiSIS Workshop, Mallorca R.Brause: Nature-inspired Robustness

6. Select robust pathway modeling
Proposition
Select robust pathway modeling
predict new signalling pathways compared to literature
identify previously unknown members of documented pathways
identify relevant groups of interacting proteins
Robustness Criteria
fault tolerance: random faults should not propagate and impede essential system functions
inherent stability: no system deviation by noise or random input, even by internal component change
NiSIS Workshop, Mallorca R.Brause: Nature-inspired Robustness

7. Nature inspired heuristics
Proposition
Nature inspired heuristics
Parallel redundancy (different pathways with same effect) e.g. muscle fibres: structural and encoding robustness
adaptive negative feedback e.g. human bone and tissue growth compensation
Nature inspired mathematical progress
stability (qualitative aspect)
sensitivity (quantitative aspect)
redundancy
of differential equations needed.
Complexity research: degrees of freedom, number of parameters !
NiSIS Workshop, Mallorca R.Brause: Nature-inspired Robustness