Abstract
An innovative feature of this book is its econocentric structure, focusing on digital designs. From the outset, econocentrism is linked with monetary exchange as the core engine of capitalism. Needless to say, monetary exchange and its ledger system will undergo significant innovations soon, sychronizing with the new stage of communication style backed by pervasiveness of quantum computing. In fact, the new coronavirus pandemic has changed lifestyles worldwide, which are unlikely ever to return to their original form. This great transformation will change the nature of the socio-economic system itself, which will be centered on digital designs. At present, money is stating to undergo a major revolution. Many books dealing with digital designs and innovations have been published, but few if any of them focus on monetary and analytical methods in the way that this present volume does. Dealing with the new attributes brought about by this great change will be beyond the scope of traditional economics. Digital tools such as blockchain, cryptocurrency, and crypt assets as well as distributive ledger systems, require new modes of analysis. First, the evolution of money and complex thinking necessary for understanding that change must be analyzed. Furthermore, the way that goods markets are mutually coordinated and the future of the labor market must be understood, points that are emphasized in the first section of the book. Second, other computational approaches to social dilemmas, crypt graphics, and the supply chain are introduced in the latter part. To facilitate understanding of the core engine of market capitalism, the detailed settlement mechanism in terms of an AI market experiment are also presented.
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Notes
- 1.
In the scheme of WEF, “we are stepping into the era of the Internet of Bodies from Things” by collecting our physical data via a range of devices that can be implanted, swallowed or worn.https://www.weforum.org/agenda/2020/06/internet-of-bodies-covid19-recovery-governance-health-data/.
- 2.
The definition of econocentrism seems not necessarily uniquely established in Oxford Dictionary, for example. Usually, econocentrism simply means the use of the principle of supply and demand at least loosely when we formalize “the value of intangible assets like human emotional development or environmental sustainability, and the monolithic implied trustworthiness of market dynamics”. The usage does not imply the strict use of the principle of supply and demand. Cited from Urban Dictionary: https://www.urbandictionary.com/define.php?term=econocentrism. In our context, the econocentrism may rather focus on the use of the principle of monetary exchange.
- 3.
Schefold then assumed that confidence returns, as the pandemic peters out, so that the option to raise interest rates again presents itself (Schefold, 2021, 16).
- 4.
- 5.
Aruka (2022) focuses on the settlement mechanism of the Bitcoin Exchange, discussing its uniqueness and commonality as compared with the stock exchange. We then introduce our new idea of digit length frequency distribution when we are interested in fully random iterated cellular automata (FRICA). Finally, we apply the length distribution to the price time series generated by the U-Mart acceleration experiment tool and examine the neutralizing effects by the change of the market transaction strategy composition, which may suggest some possible criteria whether the market may be rigged or not.
- 6.
The items described below is cited from https://www.coindesk.com/information/ethereum-smart-contracts-work.
- 7.
See Siemens’ website page titled: Automation systems for all requirements https://new.siemens.com/global/en/products/automation/systems.html.
- 8.
See Arthur (2009, 73).
- 9.
All signal processing begins with an input transducer. The input transducer takes the input signal and converts it to an electrical signal. In signal-processing applications, the transducer can take many forms. A common example of an input transducer is a microphone.
- 10.
This part summarizes (Aruka et al., 2009, 311).
- 11.
We already learned that something causal will sometimes cause chaotic behaviors if a nonlinear relationship is given. However, something causal must be necessarily condition for an exact prediction.
- 12.
More details are discussed in Wolfram Community titled Kaurov’s “Visibility Graphs: Dualism of Time Series and Networks”https://community.wolfram.com/groups/-/m/t/33771.
- 13.
In their Fig. 3 of Lacasa et al. (2008), the “first 250 values of R(t), where R is a random series of 106 data values extracted from U[0, 1]”. On the other hand, the “degree distribution P(k) of the visibility graph associated with R(t) (plotted in semilog). Although the beginning of the curve approaches the result of a Poisson process, and the tail is clearly exponential. This behavior is due to data with large values (rare events), which are the hubs”.
- 14.
This part is cited from Mathematica index. https://reference.wolfram.com/language/ref/ExponentialDistribution.html.
- 15.
The detailed relationships of not only the mentioned distribution but also the other distributions are found in Mathematica’s reference https://reference.wolfram.com/language/ref/ExponentialDistribution.html.
- 16.
See the details of the strategies employed in the U-Mart system for Chap. 11 written by Professor Nakajima.
- 17.
- 18.
Dr. Yoshihiro Nakajima, my collaborator, contributed to this interpretation. The author is thankful for his wise advice.
- 19.
The data of Nikkei225 is partly employed a part of the period from 1965 to 2021 fitted to the experimental tool period range.
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Aruka, Y. (2024). Alternative Developing Tools for Economics. In: Evolutionary Economics. Springer Texts in Business and Economics. Springer, Singapore. https://doi.org/10.1007/978-981-97-1382-0_7
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