Tokyo/Model
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(/* To establish a system following Pareto’s principle, the system must satisfy the following three cases. In our model, all nodes have the same genetic circuits and take two states, A (worker) and B (idler), depending on the surrounding circumstances. *) |
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==[[Tokyo_Tech|Abstruct]] [[Tokyo/Model|Concept & Model]] [[Tokyo/Requirements |Requirements]] [[Tokyo/Genetic circuit|Genetic_circuit]] [[Tokyo/Works|Works]] [[Tokyo/about our team|About_our_team]]== | ==[[Tokyo_Tech|Abstruct]] [[Tokyo/Model|Concept & Model]] [[Tokyo/Requirements |Requirements]] [[Tokyo/Genetic circuit|Genetic_circuit]] [[Tokyo/Works|Works]] [[Tokyo/about our team|About_our_team]]== | ||
| - | ==== To establish a system following Pareto’s principle(for example ), the system must satisfy the following three cases. In our model, all nodes have the same genetic circuits and take two states, A (worker) and B (idler), depending on the surrounding circumstances. ==== | + | ==== To establish a system following Pareto’s principle(for example [[Tokyo/Concepts|Ant society]]), the system must satisfy the following three cases. In our model, all nodes have the same genetic circuits and take two states, A (worker) and B (idler), depending on the surrounding circumstances. ==== |
'''Condition 1. Bistable state''' | '''Condition 1. Bistable state''' | ||
Revision as of 10:43, 23 October 2007
Abstruct Concept & Model Requirements Genetic_circuit Works About_our_team
To establish a system following Pareto’s principle(for example Ant society), the system must satisfy the following three cases. In our model, all nodes have the same genetic circuits and take two states, A (worker) and B (idler), depending on the surrounding circumstances.
Condition 1. Bistable state
The system is stable containing nodes A and B at certain ratio.
Condition 2. Unstable state with node A removed
Removed of node A, the system contains only node B and becomes unstable. Node B detects the removal of node A from the system and knows that there is only node B left.
Condition 3. From unstable to stable state
In an unstable state, some node B become A while the others remain B. The system then becomes stable again.
