Cities, from Information to Interaction

From physics to the social sciences, information is now seen as a fundamental component of reality. However, a form of information seems still underestimated, perhaps precisely because it is so pervasive that we take it for granted: the information encoded in the very environment we live in. We still do not fully understand how information takes the form of cities, and how our minds deal with it in order to learn about the world, make daily decisions, and take part in the complex system of interactions we create as we live together. This paper addresses three related problems that need to be solved if we are to understand the role of environmental information: (1) the physical problem: how can we preserve information in the built environment? (2) The semantic problem: how do we make environmental information meaningful? and (3) the pragmatic problem: how do we use environmental information in our daily lives? Attempting to devise a solution to these problems, we introduce a three-layered model of information in cities, namely environmental information in physical space, environmental information in semantic space, and the information enacted by interacting agents. We propose forms of estimating entropy in these different layers, and apply these measures to emblematic urban cases and simulated scenarios. Our results suggest that ordered spatial structures and diverse land use patterns encode information, and that aspects of physical and semantic information affect coordination in interaction systems.


Cities, from Information to Interaction.
Netto, V.M.; Brigatti, E.; Meirelles, J.; Ribeiro, F.L.; Pace, B.; Cacholas, C.; Sanches, P.
Entropy 2018, 20, 834.


Power and Leadership: A Complex Systems Science Approach Part I—Representation and Dynamics

Historical social narratives are dominated by the actions of powerful individuals as well as competitions for power including warfare, revolutions, and political change. Advancing our understanding of the origins, types and competitive strength of different kinds of power may yield a scaffolding for understanding historical processes and mechanisms for winning or avoiding conflicts. Michael Mann introduced a framework distinguishing four types of power: political, military, economic, and ideological. We show this framework can be justified based upon motivations of individuals to transfer decision making authority to leaders: Desire to be a member of a collective, avoiding harm due to threat, gaining benefit due to payment, acquiring a value system. Constructing models of societies based upon these types of power enables us to distinguish between social systems and describe their dynamics. Dynamical processes include (a) competition between power systems, (b) competition between powerful individuals within a power system of a society, and (c) the dynamics of values within a powerful individual. A historical trend in kinds of power systems is the progressive separation of types of power to distinct groups of individuals. In ancient empires all forms of power were concentrated in a single individual, e.g. Caesar during the Pax Romana period. In an idealized modern democratic state, the four types of power are concentrated in distinct sets of individuals. The progressive separation of the types of power suggests that in some contexts this confers a "fitness" advantage in an evolutionary process similar to the selection of biological organisms. However, individual countries may not separate power completely. The influence of wealth in politics and regulatory capture is a signature of the dominance of economic leaders, e.g. the US. Important roles of political leaders in economics and corruption are a signature of the dominance of political leaders, e.g. China. Ideological leaders dominate in theocracies, e.g. Iran. Military leaders dominate in dictatorships or countries where military leaders play a role in the selection of leaders, e.g. Egypt.


Yaneer Bar-Yam, Power and leadership: A complex systems science approach Part I—Representation and dynamics, arXiv:1811.02896 (November 7, 2018).


Senior Researcher in Complex Systems @LakesideLabs

Lakeside Labs is a research and innovation company driven by the vision to create solutions for networked systems using concepts from self-organization. To further strengthen our team, we have an opening for a senior researcher position in complex systems engineering with emphasis on robotics/drones and autonomous transportation.

* Perform outstanding research in the field of complex systems
* Publish in high-tier scientific journals and conferences
* Actively participate in research projects
* Collaborate with companies and research partners
* Take responsibility in project management
* Contribute to project proposals on a national and European level
The successful candidate will initially work, in a team of three researchers, in a European research project on design methods for cyber-physical systems with emphasis on swarm intelligence and its integration into a model-based library.


Complex Systems Postgraduate Entry Scholarship @ University of Sydney

Established in 2016, this Scholarship has been generously funded by the School of Civil Engineering to encourage and assist students with completing studies in complex systems at the University of Sydney.

Applicants must have an unconditional offer of admission for the Masters of Complex Systems within the Faculty of Engineering and Information Technologies at the University of Sydney.
Applicants must have achieved a WAM of 75 and above, or equivalent, in their previous tertiary studies.


Deadline: February 14th, 2019.


The Moral Machine experiment

With the rapid development of artificial intelligence have come concerns about how machines will make moral decisions, and the major challenge of quantifying societal expectations about the ethical principles that should guide machine behaviour. To address this challenge, we deployed the Moral Machine, an online experimental platform designed to explore the moral dilemmas faced by autonomous vehicles. This platform gathered 40 million decisions in ten languages from millions of people in 233 countries and territories. Here we describe the results of this experiment. First, we summarize global moral preferences. Second, we document individual variations in preferences, based on respondents’ demographics. Third, we report cross-cultural ethical variation, and uncover three major clusters of countries. Fourth, we show that these differences correlate with modern institutions and deep cultural traits. We discuss how these preferences can contribute to developing global, socially acceptable principles for machine ethics. All data used in this article are publicly available.


The Moral Machine experiment
Edmond Awad, Sohan Dsouza, Richard Kim, Jonathan Schulz, Joseph Henrich, Azim Shariff, Jean-François Bonnefon & Iyad Rahwan 
Nature volume 563, pages59–64 (2018)