Exogenous Rewards for Promoting Cooperation in Scale-Free Networks

The design of mechanisms that encourage pro-social behaviours in populations of self-regarding agents is recognised as a major theoretical challenge within several areas of social, life and engineering sciences. When interference from external parties is considered, several heuristics have been identified as capable of engineering a desired collective behaviour at a minimal cost. However, these studies neglect the diverse nature of contexts and social structures that characterise real-world populations. Here we analyse the impact of diversity by means of scale-free interaction networks with high and low levels of clustering, and test various interference mechanisms using simulations of agents facing a cooperative dilemma. Our results show that interference on scale-free networks is not trivial and that distinct levels of clustering react differently to each interference mechanism. As such, we argue that no tailored response fits all scale-free networks and present which mechanisms are more efficient at fostering cooperation in both types of networks. Finally, we discuss the pitfalls of considering reckless interference mechanisms.


Exogenous Rewards for Promoting Cooperation in Scale-Free Networks

Theodor Cimpeanu, The Anh Han, Francisco C. Santos

Source: arxiv.org

A map is not the territory, or is it?

‘A map is not the territory’ is a mantra introduced by the Polish-American mathematician Alfred Korzybski in an essay on the meaning of representation which he published in 1931. In it, he makes the very obvious point that an abstraction of something is not the thing itself and he uses the concept of the map to enforce this point. We all know what a map is. It is picture of the territory but with many details, in fact most details omitted. It may be similar to the thing but it can never be same. Korzybski’s thesis is a closely argued treatise about how close a representation must be to the thing it is associated with and in grappling with this problem, he implicitly defines a model, echoing to an extent the concept of the ‘digital twin’ that is preoccupying us somewhat in contemporary discussion of how we should build and use simulation models. In a previous editorial last year (Batty, 2018), I introduced the problem where I argued that such a digital twin must be an abstraction from the thing itself to which it is twinned. It may approach the thing itself but it can never be the same for the twin is a model as defined by an abstraction. Tomko and Winter (2019) took me to task in a rather gentle way for blurring this distinction in my saying that a twin is not the real thing but implying the twin needs to get as close as possible to the real thing. If we do get close, then the abstraction and the thing itself begin to merge. This does not quite reach the point where the twin is absorbed with the thing being abstracted but it does suggest that as our world – whether it be societies, cities, building complexes, etc. – evolves, then the digital landscape which hitherto we have regarded as something rather separate from the actual landscape begin to merge, producing a new landscape that is a mixture of both. We will elaborate this point below for it is intrinsic to the way in which material and digital societies relate to one another.


A map is not the territory, or is it?
Michael Batty
Environment and Planning B: Urban Analytics and City Science

Source: journals.sagepub.com

Don’t let industry write the rules for AI

Companies’ input in shaping the future of AI is essential, but they cannot retain the power they have gained to frame research on how their systems impact society or on how we evaluate the effect morally. Governments and publicly accountable entities must support independent research, and insist that industry shares enough data for it to be kept accountable.


Don’t let industry write the rules for AI

 Yochai Benkler

Nature 569, 161 (2019)

doi: 10.1038/d41586-019-01413-1

Source: www.nature.com

Can scientific productivity impact the economic complexity of countries?

The so-called index of economic complexity, based on nations’ exports, was initially proposed as an alternative to traditional macroeconomic metrics just as the scientific productivity of countries which has also been deemed as a better predictor of economic growth. Adequate scrutiny to the relationship between these two factors, however, remains little explored. This paper aims to examine the relationship between economic complexity and scientific production while identifying which areas of knowledge hold to this relationship best. By applying panel data techniques to a sample of 91 countries between 2003 and 2014, we found that scientific productivity in basic sciences and engineering has a significant positive effect on the economic complexity of countries. This relationship, however, only remains stable for high-income countries, where university-industry-government capabilities interact to stimulate and generate innovation and strategies for economic growth of firms.


Can scientific productivity impact the economic complexity of countries?

Henry Laverde-Rojas & Juan C. Correa

pp 1–16

Source: link.springer.com