New Turing-universality results in Elementary Cellular Automata in recent published paper: "Rule Primality, Minimal Generating Sets and Turing-Universality in the Causal Decomposition of Elementary Cellular Automata" by Jürgen Riedel and Hector Zenil

 

New paper discovers and proves new universality results in ECA, namely, that the Boolean composition of ECA rules 51 and 118, and 170, 15 and 118 can emulate ECA rule 110 and are thus Turing-universal coupled systems. It is introduced a 4-colour Turing-universal cellular automaton that carries the Boolean composition of 2 and 3 ECA rules emulating ECA rule 110 under multi-scale coarse-graining. They find that rules generating the ECA rulespace by Boolean composition are of low complexity and comprise prime rules implementing basic operations that when composed enable complex behaviour. They also found a candidate minimal set with only 38 ECA prime rules — and several other small sets — capable of generating all other (non-trivially symmetric) 88 ECA rules under Boolean composition.

Source: www.oldcitypublishing.com

Spatial evolutionary game theory explains how cooperative traits can survive the intense competition in biological systems. If the spatial distribution allows cooperators to interact with each other frequently, the benefits of cooperation will outweigh the losses due to exploitation by selfish organisms. However, for a cooperative behavior to get established in a system, it needs to be found initially in a sufficiently large cluster to allow a high frequency of intracooperator interactions. Since mutations are rare events, this poses the question of how cooperation can arise in a biological system in the first place. We present a simple model which captures two concepts from genetics that can explain how evolution overcomes the emergence problem. The first concept is, often in nature, a gene may not express its phenotype except under specific environmental conditions, rendering it to be a “silent” gene. The second key idea is that a neutral gene, one that does not harm or improve an organism’s survival chances, can still spread through a population if it is physically near to another gene that is positively selected. Through these two ideas, our model offers a possible solution to the fundamental problem of emergence of cooperation in biological systems.

 

The Silent Cooperator: An Epigenetic Model for Emergence of Altruistic Traits in Biological Systems
I. Hashem, D. Telen, P. Nimmegeers, and J. Van Impe

Complexity
Volume 2018, Article ID 2082037, 16 pages
https://doi.org/10.1155/2018/2082037

Source: www.hindawi.com

Low-level “adaptive” and higher-level “sophisticated” human reasoning processes have been proposed to play opposing roles in the emergence of unpredictable collective behaviors such as crowd panics, traffic jams, and market bubbles. While adaptive processes are widely recognized drivers of emergent social complexity, complementary theories of sophistication predict that incentives, education, and other inducements to rationality will suppress it. We show in a series of multiplayer laboratory experiments that, rather than suppressing complex social dynamics, sophisticated reasoning processes can drive them. Our experiments elicit an endogenous collective behavior and show that it is driven by the human ability to recursively anticipate the reasoning of others. We identify this behavior, “sophisticated flocking”, across three games, the Beauty Contest and the “Mod Game” and “Runway Game”. In supporting our argument, we also present evidence for mental models and social norms constraining how players express their higher-level reasoning abilities. By implicating sophisticated recursive reasoning in the kind of complex dynamic that it has been predicted to suppress, we support interdisciplinary perspectives that emergent complexity is typical of even the most intelligent populations and carefully designed social systems.

 

Cognitive mechanisms for human flocking dynamics
Seth Frey, Robert L. Goldstone

Journal of Computational Social Science
September 2018, Volume 1, Issue 2, pp 349–375

Source: link.springer.com

Zipf’s law states that the frequency of an observation with a given value is inversely proportional to the square of that value; Taylor’s law, instead, describes the scaling between fluctuations in the size of a population and its mean. Empirical evidence of the validity of these laws has been found in many and diverse domains. Despite the numerous models proposed to explain the presence of Zipf’s law, there is no consensus on how it originates from a microscopic process of individual dynamics without fine-tuning. Here we show that Zipf’s law and Taylor’s law can emerge from a general class of stochastic processes at the individual level, which incorporate one of two features: environmental variability, i.e., fluctuations of parameters, or correlations, i.e., dependence between individuals. Under these assumptions, we show numerically and with theoretical arguments that the conditional variance of the population increments scales as the square of the population, and that the corresponding stationary distribution of the processes follows Zipf’s law.

 

Zipf’s and Taylor’s laws

Charlotte James, Sandro Azaele, Amos Maritan, and Filippo Simini
Phys. Rev. E 98, 032408 – Published 12 September 2018

Source: journals.aps.org

Since the presentation of the radiation model, much work has been done to compare its findings with those obtained from gravitational models. These comparisons always aim at measuring the accuracy with which the models reproduce the mobility described by origin–destination matrices. This has been done at different spatial scales using different datasets, and several versions of the models have been proposed to adjust to various spatial systems. However, the models, to our knowledge, have never been compared with respect to policy testing scenarios. For this reason, here we use the models to analyse the impact of the introduction of a new transportation network, a bus rapid transport system, in the city of Teresina in Brazil. We do this by measuring the estimated variation in the trip distribution, and formulate an accessibility to employment indicator for the different zones of the city. By comparing the results obtained with the two approaches, we are able to not only better assess the goodness of fit and the impact of this intervention, but also understand reasons for the systematic similarities and differences in their predictions.

 

Measuring accessibility using gravity and radiation models
Duccio Piovani, Elsa Arcaute, Gabriela Uchoa, Alan Wilson, Michael Batty
Published 12 September 2018.DOI: 10.1098/rsos.171668

Source: rsos.royalsocietypublishing.org