holon.net - Holonic Solutions

Success! Domain holon.net was analyzed on Monday 31. October 2016!

DomainsData.org: Holonic Solutions

Title:

Holonic Solutions
Age:

19 years old
Alexa Rank:

14,838,378
Total Sites Linking In (Alexa):

9
Domain's IP Country:

United States
Status Code:

OK
IP Address:

54.69.97.136
Description:

Techniques and tools for the analysis and design of holonic systems.
Keywords:

holon, holons, holonic, holonics, holarchy, holarchies, holonisation, holonization, self-organisation, self-organization, evolution, complexity, complex systems, systems engineering, upward causation, downward causation, chaos theory, Arthur Koestler, open hierarchical systems, formal methods, distributed intelligence systems, DIS, multiagent systems, MAS, multi-agent systems, nonlinear systems, non-linear systems, Brooks, subsumption architecture, holonic manufacturing systems, HMS, nanotechnology, Drexler, Petri nets, CPN, Brooks, Design/CPN, Kurt Jensen, Standard ML, SML, ML, Coloured Petri nets, CP-nets, emergence, emergent behaviour, emergent behavior, distributed artificial intelligence, DAI, emergent systems, Australia

holon.net Whois Information:

Website Important Html Tags:

TAG
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holon, holons, holonic, holonics, holarchy, holarchies, holonisation, holonization, self-organisation, self-organization, evolution, complexity, complex systems, systems engineering, upward causation, downward causation, chaos theory, Arthur Koestler, open hierarchical systems, formal methods, distributed intelligence systems, DIS, multiagent systems, MAS, multi-agent systems, nonlinear systems, non-linear systems, Brooks, subsumption architecture, holonic manufacturing systems, HMS, nanotechnology, Drexler, Petri nets, CPN, Brooks, Design/CPN, Kurt Jensen, Standard ML, SML, ML, Coloured Petri nets, CP-nets, emergence, emergent behaviour, emergent behavior, distributed artificial intelligence, DAI, emergent systems, Australia
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Holonic Solutions
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References
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The processes of evolution and self-organisation demonstrated in nature are responsible for the development of the most complex holonic systems in operation today. One can learn from and adapt these processes;
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System size and complexity are on the increase in all areas of systems engineering. Some understanding of upward and downward causation (and emergence, chaos, stability etc.) is essential if we wish to predict or exploit - and so design for - desirable complex system behaviour;
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In
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Koestler, A.,

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