## Ensemble Modeling: Inference from Small Scale Properties to Large Scale Systems |

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advertising behavior space biological Boolean transformations brand loyalty Chapter cographic computed connectance consider control systems cycle length cycle space cycles of length cyclic decision theory defined density of l's detail disclosure length discussion distribution dynamics effective elements ensemble approach equivalence classes examine example expected number extended threshold forced value forcing inputs fully delayed search fully random gene genetic given Hamming distance Hence input span input vectors internal homogeneity interpretation Kauffman nets Lemma lexicographic order management by exception mapping value matrix modeling context Mulligan stew number of cycles number of inputs number of mappings organization organizational particular primary persuasion produced random nets real world rows run-in length sampling simulation small scale properties small-scale specific stability Statistical stone soup subset sufficient model suggest switching net models theoretical theory tion trajectory typical University of Connecticut variables Walker and Ashby