ISSN : 0891-2513
Published by: Wolfram Research, Inc. (10.25088)
Total articles ≅ 259
Latest articles in this journal
Complex Systems, Volume 30, pp 415-439; https://doi.org/10.25088/complexsystems.30.3.415
This paper proposes the synthesis of single length cycle, single attractor cellular automata (SACAs) for arbitrary length. The n-cell single length cycle, single attractor cellular automaton (SACA), synthesized in linear time O(n), generates a pattern and finally settles to a point state called the single length cycle attractor state. An analytical framework is developed around the graph-based tool referred to as the next state transition diagram to explore the properties of SACA rules for three-neighborhood, one-dimensional cellular automata. This enables synthesis of an (n+1)-cell SACA from the available configuration of an n-cell SACA in constant time and an (n+m)-cell SACA from the available configuration of n-cell and m-cell SACAs also in constant time.
Complex Systems, Volume 30, pp 273-296; https://doi.org/10.25088/complexsystems.30.3.273
We compare the statistical distributions of the geometrical properties of road networks for two representative datasets under different levels of planning: the cities comprising Metropolitan Manila show the conditions under bottom-up self-organized growth, while Brasilia and the Australian Capital Territory centered at Canberra represent the case of strict top-down planning. The distribution of segmented areas of the cities shows a dual power-law behavior, with the larger areas following the ∼1.9 scaling exponent observed in other cities, while the smaller areas show a lower exponent of ∼0.5, believed to be due to practical considerations. While all cities are found to favor the formation of straight road segments, the planned city roads have a preponderance of sinuous roads, with sinuosities approaching π. A simple model based on a nearest-neighbor directed branching coupled with sectional grid formations is proposed to capture the nontrivial statistical features observed.
Complex Systems, Volume 30, pp 347-373; https://doi.org/10.25088/complexsystems.30.3.347
Managing diversity is a challenging problem for organizations and governments. Diversity in a population may be of two kinds—acquired and innate. The former refers to diversity acquired by pre-existing social or organizational environments, attracting employees or immigrants because of their wealth and opportunities. Innate diversity, on the other hand, refers to a collection of pre-existing communities having to interact with one another and to build an overarching social or organizational identity. While acquired diversity has a prior element of common identity, innate diversity needs to build a common identity from a number of disparate regional or local identities. Diversity in any large population may have different extents of acquired and innate elements. In this paper, innate and acquired diversity are modeled in terms of two factors, namely: insularity and homophily, respectively. Insularity is the tendency of agents to act cooperatively only with others from the same community, which is often the primary challenge of innate diversity; while homophily is the tendency of agents to prefer members from their own community to start new social or business connections, which is often the primary challenge in acquired diversity. The emergence of network structure is studied when insularity and homophily are varied. In order to promote cooperation in a diverse population, the role played by a subset of agents called “global” agents who are not affected by homophily and insularity considerations is also studied. Simulation results show several interesting emergent properties. While the global agents are shown to acquire high betweenness, they are by no means the wealthiest or the most powerful in the network. However, the presence of global agents is important for the regional agents whose own wealth prospects increase because of their interaction with global agents.
Complex Systems, Volume 30, pp 391-413; https://doi.org/10.25088/complexsystems.30.3.391
This review article focuses on studying problems of observability and controllability of cellular automata (CAs) considered in the context of control theory, an important feature of which is the adoption of a state-space model. Our work first consists in generalizing the obtained results to systems described by CAs considered as the discrete counterpart of partial differential equations, and in exploring possible approaches to prove controllability and observability. After having introduced the notion of control and observation in cellular automata models, in a similar way to the case of discrete-time distributed parameter systems, we investigate these key concepts of control theory in the case of complex systems. For the controllability issue, the Boolean class is particularly studied and applied to the regional case, while the observability is approached in the general case and related to the reconstructibility problem for linear or nonlinear CAs.
Complex Systems, Volume 30, pp 297-321; https://doi.org/10.25088/complexsystems.30.3.297
An agent-based model was developed to study outbreaks and outbreak control for COVID-19, mainly in urban communities. Rules for people’s interactions and virus infectiousness were derived based on previous sociology studies and recently published data-driven analyses of COVID-19 epidemics. The calculated basic reproduction number of epidemics from the developed model coincided with reported values. There were three control measures considered in this paper: social distancing, self-quarantine and community quarantine. Each control measure was assessed individually at first. Later on, an artificial neural network was used to study the effects of different combinations of control measures. To help quantify the impacts of self-quarantine and community quarantine on outbreak control, both were scaled respectively. The results showed that self-quarantine was more effective than the others, but any individual control measure was ineffective in controlling outbreaks in urban communities. The results also showed that a high level of self-quarantine and general community quarantine, assisted with social distancing, would be recommended for outbreak control.
Complex Systems, Volume 30, pp 239-272; https://doi.org/10.25088/complexsystems.30.3.239
One-dimensional cellular automata evolutions with both temporal and spatial periodicity are studied. The main objective is to investigate the longest temporal periods among all two-neighbor rules, with a fixed spatial period σ and number of states n. When σ = 2, 3, 4 or 6, and the rules are restricted to be additive, the longest period can be expressed as the exponent of the multiplicative group of an appropriate ring. Non-additive rules are also constructed with temporal period on the same order as the trivial upper bound n σ . Experimental results, open problems and possible extensions of the results are also discussed.
Complex Systems, Volume 30, pp 375-390; https://doi.org/10.25088/complexsystems.30.3.375
A puzzle lies behind password authentication (PA) and blockchain proof of work (PoW). A cryptographic hash function is commonly used to implement them. The potential problem with secure hash functions is their complexity and rigidity. We explore the use of complex systems constructs such as a cellular automaton (CA) to provide puzzle functionality. The analysis shows that computational irreducibility and sensitivity to initial state phenomena are enough to create simple puzzle systems that can be used for PA and PoW. Moreover, we present puzzle schemata using CA and n-body problems.
Complex Systems, Volume 30, pp 323-346; https://doi.org/10.25088/complexsystems.30.3.323
The recent worldwide epidemic of COVID-19 disease, for which there are no medications to cure it and the vaccination is still at an early stage, led to the adoption of public health measures by governments and populations in most of the affected countries to avoid the contagion and its spread. These measures are known as nonpharmaceutical interventions (NPIs), and their implementation clearly produces social unrest as well as greatly affects the economy. Frequently, NPIs are implemented with an intensity quantified in an ad hoc manner. Control theory offers a worthwhile tool for determining the optimal intensity of the NPIs in order to avoid the collapse of the healthcare system while keeping them as low as possible, yielding concrete guidance to policymakers. A simple controller, which generates a control law that is easy to calculate and to implement is proposed. This controller is robust to large parametric uncertainties in the model used and to some level of noncompliance with the NPIs.
Complex Systems, Volume 30, pp 111-132; https://doi.org/10.25088/complexsystems.30.2.111
In contrast to many investigations of cellular automata with regard to their ability to accept inputs under certain time constraints, in this paper we are studying cellular automata with regard to their ability to generate strings in real time. Structural properties such as speedup results and closure properties are investigated. On the one hand, constructions for the closure under intersection, reversal and length-preserving homomorphism are presented, whereas on the other hand the nonclosure under union, complementation and arbitrary homomorphism are obtained. Finally, decidability questions such as emptiness, finiteness, equivalence, inclusion, regularity and context-freeness are addressed.
Complex Systems, Volume 30, pp 187-203; https://doi.org/10.25088/complexsystems.30.2.187
This paper develops a formal logic, named L CA , targeting modeling of one-dimensional binary cellular automata. We first develop the syntax of L CA , then give semantics to L CA in the domain of all binary strings. Then the elementary cellular automata and four-neighborhood binary cellular automata are shown as models of the logic. These instances point out that there are other models of L CA . Finally it is proved that any one-dimensional binary cellular automaton is a model of the proposed logic.