Greedy algorithms and Zipf laws
We consider a simple model of firm/city/etc growth based on a multi-item criterion: whenever entity B fares better than entity A on a subset of M items out of K, the agent originally in A moves to B. We solve the model analytically in the cases K = 1 and . The resulting stationary distribution of...
| প্রধান লেখক: | , |
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| বিন্যাস: | Journal article |
| ভাষা: | English |
| প্রকাশিত: |
IOP Publishing
2018
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| সংক্ষিপ্ত: | We consider a simple model of firm/city/etc growth based on a multi-item criterion: whenever entity B fares better than entity A on a subset of M items out of K, the agent originally in A moves to B. We solve the model analytically in the cases K = 1 and . The resulting stationary distribution of sizes is generically a Zipf-law provided M > K/2. When , no selection occurs and the size distribution remains thin-tailed. In the special case M = K, one needs to regularize the problem by introducing a small 'default' probability phgr. We find that the stationary distribution has a power-law tail that becomes a Zipf-law when . The approach to the stationary state can also be characterized, with strong similarities with a simple 'aging' model considered by Barrat and Mézard. |
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