Abstract
This last paper of the collection is mainly thought of as a pretext to trigger hands-on experience in the interested reader. It will present a “simple” model, some preliminary results and a series of issues that the model could address with “some” modification.
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Notes
Clearly, we are not suggesting that the delay in the Italian development was solely due to the lack of readily available coal, only that it certainly played a role
See Bruun and Luna in this volume for a brief description of that model and the relevant reference
The term is imported from the neural-network literature
Those instances for which the function is TRUE
We will explain this constraint momentarily.
One of the instances in table 11.1 where a is the value taken by the variable A and f3 is the value taken by the variable B.
A particular structure and one set of weights
Initially the program had been written in Mathematica. Then we re-wrote the same routine in C with great gains in performance, but we could reach only the results for 6-worker organizations in an acceptable time
There is obviously always a third possibility: a mistake in the code. Rather than excluding this event superciliously, we suggest that such an elusive “bug” might have been introduced on purpose by the wicked mind of these authors as a challenge for the reader.
Penrose, E. 1959, The Theory of the Growth of the Firm, Oxford University Press, Oxford
The other parameters were set as follows: updHC = 0, seed = 50, daysInMonth = 20.
represented by our mechanism for the creation of enterprises
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Luna, F., Perrone, A. (2000). The Coevolution of Human Capital and Firm Structure. In: Luna, F., Stefansson, B. (eds) Economic Simulations in Swarm: Agent-Based Modelling and Object Oriented Programming. Advances in Computational Economics, vol 14. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4641-2_11
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