Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.
Sampling of Temporal Networks: Methods and Biases
Luis E C Rocha, Naoki Masuda, Petter Holme
Asimov’s three laws of robotics, which were shaped in the literary work of Isaac Asimov (1920–1992) and others, define a crucial code of behavior that fictional autonomous robots must obey as a condition for their integration into human society. While, general implementation of these laws in robots is widely considered impractical, limited-scope versions have been demonstrated and have proven useful in spurring scientific debate on aspects of safety and autonomy in robots and intelligent systems. In this work, we use Asimov’s laws to examine these notions in molecular robots fabricated from DNA origami. We successfully programmed these robots to obey, by means of interactions between individual robots in a large population, an appropriately scoped variant of Asimov’s laws, and even emulate the key scenario from Asimov’s story “Runaround,” in which a fictional robot gets into trouble despite adhering to the laws. Our findings show that abstract, complex notions can be encoded and implemented at the molecular scale, when we understand robots on this scale on the basis of their interactions.
Molecular Robots Obeying Asimov’s Three Laws of Robotics
Gal A. Kaminka, Rachel Spokoini-Stern, Yaniv Amir, Noa Agmon and Ido Bachelet
Volume 23 | Issue 3 | Summer 2017
Amoeba, a computer platform inspired by the Tierra system, is designed to study the generation of self-replicating sequences of machine operations (opcodes) from a prebiotic world initially populated by randomly selected opcodes. Point mutations drive opcode sequences to become more fit as they compete for memory and CPU time. Significant features of the Amoeba system include the lack of artificial encapsulation (there is no write protection) and a computationally universal opcode basis set. Amoeba now includes two additional features: pattern-based addressing and injecting entropy into the system. It was previously thought such changes would make it highly unlikely that an ancestral replicator could emerge from a fortuitous combination of randomly selected opcodes. Instead, Amoeba shows a far richer emergence, exhibiting a self-organization phase followed by the emergence of self-replicators. First, the opcode basis set becomes biased. Second, short opcode building blocks are propagated throughout memory space. Finally, prebiotic building blocks can combine to form self-replicators. Self-organization is quantified by measuring the evolution of opcode frequencies, the size distribution of sequences, and the mutual information of opcode pairs.
Self-Replicators Emerge from a Self-Organizing Prebiotic Computer World
B. Greenbaum and A. N. Pargellis
Volume 23 | Issue 3 | Summer 2017
We define rules for cellular automata played on quasiperiodic tilings of the plane arising from the multigrid method in such a way that these cellular automata are isomorphic to Conway’s Game of Life. Although these tilings are nonperiodic, determining the next state of each tile is a local computation, requiring only knowledge of the local structure of the tiling and the states of finitely many nearby tiles. As an example, we show a version of a “glider” moving through a region of a Penrose tiling. This constitutes a potential theoretical framework for a method of executing computations in non-periodically structured substrates such as quasicrystals.
A Game of Life on Penrose tilings
Duane A. Bailey, Kathryn A. Lindsey
The spread of opinions, memes, diseases, and “alternative facts” in a population depends both on the details of the spreading process and on the structure of the social and communication networks on which they spread. One feature that can change spreading dynamics substantially is heterogeneous behavior among different types of individuals in a social network. In this paper, we explore how anti-establishment nodes (e.g., hipsters) influence spreading dynamics of two competing products. We consider a model in which spreading follows a deterministic rule for updating node states in which an adjustable fraction pHip of the nodes in a network are hipsters, who always choose to adopt the product that they believe is the less popular of the two. The remaining nodes are conformists, who choose which product to adopt by considering only which products their immediate neighbors have adopted. We simulate our model on both synthetic and real networks, and we show that the hipsters have a major effect on the final fraction of people who adopt each product: even when only one of the two products exists at the beginning of the simulations, a very small fraction of hipsters in a network can still cause the other product to eventually become more popular. Our simulations also demonstrate that a time delay τ in the knowledge of the product distribution in a population has a large effect on the final distribution of product adoptions. Our simple model and analysis may help shed light on the road to success for anti-establishment choices in elections, as such success — and qualitative differences in final outcomes between competing products, political candidates, and so on — can arise rather generically from a small number of anti-establishment individuals and ordinary processes of social influence on normal individuals.
Hipsters on Networks: How a Small Group of Individuals Can Lead to an Anti-Establishment Majority
Jonas S. Juul, Mason A. Porter