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Where Next for Microbiome Research?

The development of high-throughput sequencing technologies has transformed our capacity to investigate the composition and dynamics of the microbial communities that populate diverse habitats. Over the past decade, these advances have yielded an avalanche of metagenomic data. The current stage of “van Leeuwenhoek”–like cataloguing, as well as functional analyses, will likely accelerate as DNA and RNA sequencing, plus protein and metabolic profiling capacities and computational tools, continue to improve. However, it is time to consider: what’s next for microbiome research? The short pieces included here briefly consider the challenges and opportunities awaiting microbiome research.


Waldor MK, Tyson G, Borenstein E, Ochman H, Moeller A, et al. (2015) Where Next for Microbiome Research? PLoS Biol 13(1): e1002050. http://dx.doi.org/10.1371/journal.pbio.1002050 ;

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NETWORKED MINDS: Where human evolution is heading

Having studied the technological and social forces shaping our societies, we are now turning to the evolutionary forces. Among the millions of species on earth, humans are truly unique. 
What is the recipe of our success? What makes us special? How do we decide? How will we further evolve? What will our role be, when algorithms, computers, machines, and robots are getting ever more powerful? How will our societies change?


http://futurict.blogspot.ie/2014/12/networked-minds-where-human-evolution.html

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Estimating Food Consumption and Poverty Indices with Mobile Phone Data

Recent studies have shown the value of mobile phone data to tackle problems related to economic development and humanitarian action. In this research, we assess the suitability of indicators derived from mobile phone data as a proxy for food security indicators. We compare the measures extracted from call detail records and airtime credit purchases to the results of a nationwide household survey conducted at the same time. Results show high correlations (> .8) between mobile phone data derived indicators and several relevant food security variables such as expenditure on food or vegetable consumption. This correspondence suggests that, in the future, proxies derived from mobile phone data could be used to provide valuable up-to-date operational information on food security throughout low and middle income countries.


Estimating Food Consumption and Poverty Indices with Mobile Phone Data
Adeline Decuyper, Alex Rutherford, Amit Wadhwa, Jean-Martin Bauer, Gautier Krings, Thoralf Gutierrez, Vincent D. Blondel, Miguel A. Luengo-Oroz

http://arxiv.org/abs/1412.2595

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SOCIAL FORCES: Revealing the causes of success or disaster

SOCIAL FORCES: Revealing the causes of success or disaster | Papers | Scoop.it

We have seen that self-organizing systems can be very effective and efficient, but their macro-level behavior crucially depends on the interaction rules, interaction strength, and institutional settings. To get things right, it's important to understand the factors that drive the dynamics of the system. 


http://futurict.blogspot.ie/2014/12/social-forces-revealing-causes-of.html

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Computational fact checking from knowledge networks

Traditional fact checking by expert journalists cannot keep up with the enormous volume of information that is now generated online. Computational fact checking may significantly enhance our ability to evaluate the veracity of dubious information. Here we show that the complexities of human fact checking can be approximated quite well by finding the shortest path between concept nodes under properly defined semantic proximity metrics on knowledge graphs. Framed as a network problem this approach is feasible with efficient computational techniques. We evaluate this approach by examining tens of thousands of claims related to history, entertainment, geography, and biographical information using a public knowledge graph extracted from Wikipedia. Statements independently known to be true consistently receive higher support via our method than do false ones. These findings represent a significant step toward scalable computational fact-checking methods that may one day mitigate the spread of harmful misinformation.


Computational fact checking from knowledge networks
Giovanni Luca Ciampaglia, Prashant Shiralkar, Luis M. Rocha, Johan Bollen, Filippo Menczer, Alessandro Flammini

http://arxiv.org/abs/1501.03471

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The Fundamental Scale of Descriptions

The complexity of a system description is a function of the entropy of its symbolic description. Prior to computing the entropy of the system description, an observation scale has to be assumed. In natural language texts, typical scales are binary, characters, and words. However, considering languages as structures built around certain preconceived set of symbols, like words or characters, is only a presumption. This study depicts the notion of the Description Fundamental Scale as a set of symbols which serves to analyze the essence a language structure. The concept of Fundamental Scale is tested using English and MIDI music texts by means of an algorithm developed to search for a set of symbols, which minimizes the system observed entropy, and therefore best expresses the fundamental scale of the language employed. Test results show that it is possible to find the Fundamental Scale of some languages. The concept of Fundamental Scale, and the method for its determination, emerges as an interesting tool to facilitate the study of languages and complex systems.


The Fundamental Scale of Descriptions
Gerardo Febres

http://arxiv.org/abs/1412.8268

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Complexity Digest's comment, April 1, 2015 11:35 AM
Just published in http://www.mdpi.com/1099-4300/17/4/1606
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Follow the Leader: Herding Behavior in Heterogeneous Populations

Here we study the emergence of spontaneous leadership in large populations. In standard models of opinion dynamics, herding behavior is only obeyed at the local scale due to the interaction of single agents with their neighbors; while at the global scale, such models are governed by purely diffusive processes. Surprisingly, in this paper we show that the combination of a strong separation of time scales within the population and a hierarchical organization of the influences of some agents on the others induces a phase transition between a purely diffusive phase, as in the standard case, and a herding phase where a fraction of the agents self-organize and lead the global opinion of the whole population.


Follow the Leader: Herding Behavior in Heterogeneous Populations
Guillem Mosquera-Donate, Marian Boguna

http://arxiv.org/abs/1412.7427

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Big Questions Come In Bundles, Hence They Should Be Tackled Systemically

Problems come in all kinds and sizes. Small problems call for the use of known tools found in circumscribed fields, whereas big problems call for further research, which may require breaching disciplinary walls. This is because every small problem concerns some separable system whose components are so weakly linked with one another, that it may be reduced to an aggregate, at least to a first approximation.
I submit that (a) every problem concerns some system, and (b) analysis works only provided the system components are so loosely linked, that they can be treated as if they were isolated items. These methodological assumptions are key principles of systemism, the philosophy first expounded by d’Holbach in the 18th century, and rescued by Bertalanffy and his companions in the general systems movement in the last century.
Systems and systemism are so little known in the philosophical community, that the vast majority of philosophical dictionaries have ignored them. By contrast, all scientists and technologists have practiced systemism – except when they failed for having adopted either of the alternatives to systemism, namely atomism and holism.
A number of examples taken from contemporary science and technology are analyzed, from the entanglement typical of quantum physics to the design of social policies. Along the way we define the concept of a system, and note that (a) analysis is the dual of synthesis rather than its opposite; (b) systemism should not be mistaken for holism, because the former recommends combining the bottom-up with the top-down strategies; (c) systemism encourages the convergence or fusion of disciplines rather than reductionism. The recent replacement of GDP with more complex social indicators as the measure of social progress is regarded as a victory of the systemic view of society.
Finally, I argue that systemism is no less than a component of the philosophical matrix of scientific and technological research, along with epistemological realism, ontological materialism, scientism, and humanism. I also argue in favor of Anatol Rapoport’s view, that systems theory is not a theory proper but a viewpoint or approach that helps pose problems and place them in their context.


Big Questions Come In Bundles, Hence They Should Be Tackled Systemically
Mario Bunge

http://www.systema-journal.org/article/view/346

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Collective behaviors and networks

The goal of this thematic series is to provide a discussion venue about recent advances in the study of networks and their applications to the study of collective behavior in socio-technical systems. The series includes contributions exploring the intersection between data-driven studies of complex networks and agent-based models of collective social behavior. Particular attention is devoted to topics aimed at understanding social behavior through the lens of data about technology-mediated communication. These include: modeling social dynamics of attention and collaboration, characterizing online group formation and evolution, and studying the emergence of roles and interaction patterns in social media environments.


Collective behaviors and networks
Giovanni Luca Ciampaglia, Emilio Ferrara and Alessandro Flammini

EPJ Data Science 2014, 3:37  http://dx.doi.org/10.1140/epjds/s13688-014-0037-6

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Yellowstone Wolves and the Forces That Structure Natural Systems

Yellowstone Wolves and the Forces That Structure Natural Systems | Papers | Scoop.it
Since their introduction in 1995 and 1996, wolves have had effects on Yellowstone that ripple across the entire structure of the food web that defines biodiversity in the Northern Rockies ecosystem. Ecological interpretations of the wolves have generated a significant amount of debate about the relative strength of top-down versus bottom-up forces in determining herbivore and vegetation abundance in Yellowstone. Debates such as this are central to the resolution of broader debates about the role of natural enemies and climate as forces that structure food webs and modify ecosystem function. Ecologists need to significantly raise the profile of these discussions; understanding the forces that structure food webs and determine species abundance and the supply of ecosystem services is one of the central scientific questions for this century; its complexity will require new minds, new mathematics, and significant, consistent funding.


Dobson AP (2014) Yellowstone Wolves and the Forces That Structure Natural Systems. PLoS Biol 12(12): e1002025. http://dx.doi.org/10.1371/journal.pbio.1002025

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Coevolution Drives the Emergence of Complex Traits and Promotes Evolvability

Over billions of years, life has evolved into the extraordinarily diverse and complex organisms that populate the Earth today. Although evolution often proceeds toward increasing complexity, more complex traits do not necessarily make organisms more fit. So when and why is greater complexity favored? One hypothesis is that antagonistic coevolution between hosts and parasites can drive the evolution of more complex traits by promoting arms races with increased defenses and counter-defenses. Here, by using populations of self-replicating host computer programs and parasitic programs, which steal processing power from their hosts, we demonstrated that coevolution promotes complexity and dissected how it does so. Instead of simple escalation, we found that a diversity of coevolving lineages must arise for coevolution to drive complex traits. Surprisingly, coevolution had a second effect; it promoted the evolution of more evolvable hosts. As a consequence, mutations in the evolved host genomes that confer resistance to parasites occur at high rates, which help the coevolved hosts outrun their parasites. Our experiments with an artificial system demonstrate how the naturally ubiquitous process of coevolution can promote complexity and favor evolvability.


Zaman L, Meyer JR, Devangam S, Bryson DM, Lenski RE, et al. (2014) Coevolution Drives the Emergence of Complex Traits and Promotes Evolvability. PLoS Biol 12(12): e1002023. http://dx.doi.org/10.1371/journal.pbio.1002023

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Quantifying Natural and Artificial Intelligence in Robots and Natural Systems with an Algorithmic Behavioural Test

One of the most important aims of the fields of robotics, artificial intelligence and artificial life is the design and construction of systems and machines as versatile and as reliable as living organisms at performing high level human-like tasks. But how are we to evaluate artificial systems if we are not certain how to measure these capacities in living systems, let alone how to define life or intelligence? Here I survey a concrete metric towards measuring abstract properties of natural and artificial systems, such as the ability to react to the environment and to control one's own behaviour.


Quantifying Natural and Artificial Intelligence in Robots and Natural Systems with an Algorithmic Behavioural Test
Hector Zenil

http://arxiv.org/abs/1412.6703

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Human-Data Interaction: The Human Face of the Data-Driven Society

The increasing generation and collection of personal data has created a complex ecosystem, often collaborative but sometimes combative, around companies and individuals engaging in the use of these data. We propose that the interactions between these agents warrants a new topic of study: Human-Data Interaction (HDI). In this paper we discuss how HDI sits at the intersection of various disciplines, including computer science, statistics, sociology, psychology and behavioural economics. We expose the challenges that HDI raises, organised into three core themes of legibility, agency and negotiability, and we present the HDI agenda to open up a dialogue amongst interested parties in the personal and big data ecosystems.


Human-Data Interaction: The Human Face of the Data-Driven Society
Richard Mortier, Hamed Haddadi, Tristan Henderson, Derek McAuley, Jon Crowcroft

http://arxiv.org/abs/1412.6159

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A Unifying Theory for Scaling Laws of Human Populations

The spatial distribution of people exhibits clustering across a wide range of scales, from household to continental  scales. Empirical data indicates simple power-law scalings for the size distribution of cities (known as Zipf's law), the geographic distribution of friends, and the population density fluctuations as a function of scale. We derive a simple statistical model that explains all of these scaling laws based on a single unifying principle involving the random spatial growth of clusters of people on all scales. The model makes important new predictions for the spread of diseases and other social phenomena.


A Unifying Theory for Scaling Laws of Human Populations
Henry W. Lin, Abraham Loeb

http://arxiv.org/abs/1501.00738

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Zeke Robinson's curator insight, March 23, 2015 9:57 PM

I did not know about this law until now and I would like to get to know it better.

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Why It’s Good To Be Wrong

Why It’s Good To Be Wrong | Papers | Scoop.it

That human beings can be mistaken in anything they think or do is a proposition known as fallibilism. Stated abstractly like that, it is seldom contradicted. Yet few people have ever seriously believed it, either.

That our senses often fail us is a truism; and our self-critical culture has long ago made us familiar with the fact that we can make mistakes of reasoning too. But the type of fallibility that I want to discuss here would be all-pervasive even if our senses were as sharp as the Hubble Telescope and our minds were as logical as a computer. It arises from the way in which our ideas about reality connect with reality itself—how, in other words, we can create knowledge, and how we can fail to.

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The multilayer temporal network of public transport in Great Britain

The multilayer temporal network of public transport in Great Britain | Papers | Scoop.it

Despite the widespread availability of information concerning public transport coming from different sources, it is extremely hard to have a complete picture, in particular at a national scale. Here, we integrate timetable data obtained from the United Kingdom open-data program together with timetables of domestic flights, and obtain a comprehensive snapshot of the temporal characteristics of the whole UK public transport system for a week in October 2010. In order to focus on multi-modal aspects of the system, we use a coarse graining procedure and define explicitly the coupling between different transport modes such as connections at airports, ferry docks, rail, metro, coach and bus stations. The resulting weighted, directed, temporal and multilayer network is provided in simple, commonly used formats, ensuring easy access and the possibility of a straightforward use of old or specifically developed methods on this new and extensive dataset.


The multilayer temporal network of public transport in Great Britain
Riccardo Gallotti & Marc Barthelemy

Scientific Data, Published online: 6 January 2015; | http://dx.doi.org/10.1038/sdata.2014.56

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A Rosetta Stone for Nature’s Benefits to People

After a long incubation period, the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) is now underway. Underpinning all its activities is the IPBES Conceptual Framework (CF), a simplified model of the interactions between nature and people. Drawing on the legacy of previous large-scale environmental assessments, the CF goes further in explicitly embracing different disciplines and knowledge systems (including indigenous and local knowledge) in the co-construction of assessments of the state of the world’s biodiversity and the benefits it provides to humans. The CF can be thought of as a kind of “Rosetta Stone” that highlights commonalities between diverse value sets and seeks to facilitate crossdisciplinary and crosscultural understanding. We argue that the CF will contribute to the increasing trend towards interdisciplinarity in understanding and managing the environment. Rather than displacing disciplinary science, however, we believe that the CF will provide new contexts of discovery and policy applications for it.


Díaz S, Demissew S, Joly C, Lonsdale WM, Larigauderie A (2015) A Rosetta Stone for Nature’s Benefits to People. PLoS Biol 13(1): e1002040. http://dx.doi.org/10.1371/journal.pbio.1002040


Complexity Digest's insight:

See Also http://www.ipbes.net/

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Characterizing the Google Books corpus: Strong limits to inferences of socio-cultural and linguistic evolution

It is tempting to treat frequency trends from Google Books data sets as indicators for the true popularity of various words and phrases. Doing so allows us to draw novel conclusions about the evolution of public perception of a given topic, such as time and gender. However, sampling published works by availability and ease of digitization leads to several important effects. One of these is the surprising ability of a single prolific author to noticeably insert new phrases into a language. A greater effect arises from scientific texts, which have become increasingly prolific in the last several decades and are heavily sampled in the corpus. The result is a surge of phrases typical to academic articles but less common in general, such as references to time in the form of citations. Here, we highlight these dynamics by examining and comparing major contributions to the statistical divergence of English data sets between decades in the period 1800--2000. We find that only the English Fiction data set from the second version of the corpus is not heavily affected by professional texts, in clear contrast to the first version of the fiction data set and both unfiltered English data sets. Our findings emphasize the need to fully characterize the dynamics of the Google Books corpus before using these data sets to draw broad conclusions about cultural and linguistic evolution.


Characterizing the Google Books corpus: Strong limits to inferences of socio-cultural and linguistic evolution
Eitan Adam Pechenick, Christopher M. Danforth, Peter Sheridan Dodds

http://arxiv.org/abs/1501.00960

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Defensive complexity in antagonistic coevolution

One strategy for winning a coevolutionary struggle is to evolve rapidly. Most of the literature on host-pathogen coevolution focuses on this phenomenon, and looks for consequent evidence of coevolutionary arms races. An alternative strategy, less often considered in the literature, is to deter rapid evolutionary change by the opponent. To study how this can be done, we construct an evolutionary game between a controller that must process information, and an adversary that can tamper with this information processing. In this game, a species can foil its antagonist by processing information in a way that is hard for the antagonist to manipulate. We show that the structure of the information processing system induces a fitness landscape on which the adversary population evolves, and that complex processing logic is required to make that landscape rugged. Drawing on the rich literature concerning rates of evolution on rugged landscapes, we show how a species can slow adaptive evolution in the adversary population. We suggest that this type of defensive complexity on the part of the vertebrate adaptive immune system may be an important element of coevolutionary dynamics between pathogens and their vertebrate hosts.


Defensive complexity in antagonistic coevolution
Erick Chastain, Rustom Antia, Carl T. Bergstrom

http://arxiv.org/abs/1203.4601

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Computational Aspects of Ancient Social Heterarchies: Learning how to Address Contemporary Global Challenges

As hierarchically and centrally controlled computational systems, contemporary political systems have limitations in their information processing and action capacities to face the current social crises and challenges. In contrast, some older cultures whose political structure was more heterarchically organized, such as found in pre-Hispanic Colombia, were adaptive even without advanced scientific knowledge and without powerful top-down control. In this context, we propose that creating and analyzing computer models of their decentralized processes of management can provide a broader perspective on the possibilities of political organization. In terms of self-optimization, this approach seeks the promotion of social systems with a balance of flexibility and robustness, i.e., systems that do not rely on the current ideal of rule-based control of all systemic aspects.


Computational Aspects of Ancient Social Heterarchies: Learning how to Address Contemporary Global Challenges
Nathalie Mezza-Garcia, Tom Froese, Nelson Fernández

Journal of Sociocybernetics Vol 12, No 1/2 (2014) 

https://papiro.unizar.es/ojs/index.php/rc51-jos/article/view/797


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The Strange Inevitability of Evolution

The Strange Inevitability of Evolution | Papers | Scoop.it
Natural selection supplies an incredibly powerful way of pruning variation into effective solutions to the challenges of the environment. But it can’t explain where all that variation came from. As the biologist Hugo de Vries wrote in 1905, “natural selection may explain the survival of the fittest, but it cannot explain the arrival of the fittest.” Over the past several years, Wagner and a handful of others have been starting to understand the origins of evolutionary innovation. Thanks to their findings so far, we can now see not only how Darwinian evolution works but why it works: what makes it possible.

(...)

These ideas suggest that evolvability and openness to innovation are features not just of life but of information itself. That is a view long championed by Schuster’s sometime collaborator, Nobel laureate chemist Manfred Eigen, who insists that Darwinian evolution is not merely the organizing principle of biology but a “law of physics,” an inevitable result of how information is organized in complex systems. And if that’s right, it would seem that the appearance of life was not a fantastic fluke but almost a mathematical inevitability.


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Social networks in primates: smart and tolerant species have more efficient networks

Network optimality has been described in genes, proteins and human communicative networks. In the latter, optimality leads to the efficient transmission of information with a minimum number of connections. Whilst studies show that differences in centrality exist in animal networks with central individuals having higher fitness, network efficiency has never been studied in animal groups. Here we studied 78 groups of primates (24 species). We found that group size and neocortex ratio were correlated with network efficiency. Centralisation (whether several individuals are central in the group) and modularity (how a group is clustered) had opposing effects on network efficiency, showing that tolerant species have more efficient networks. Such network properties affecting individual fitness could be shaped by natural selection. Our results are in accordance with the social brain and cultural intelligence hypotheses, which suggest that the importance of network efficiency and information flow through social learning relates to cognitive abilities.


Social networks in primates: smart and tolerant species have more efficient networks
• Cristian Pasquaretta, Marine Levé, Nicolas Claidière, Erica van de Waal, Andrew Whiten, Andrew J. J. MacIntosh, Marie Pelé, Mackenzie L. Bergstrom, Christèle Borgeaud, Sarah F. Brosnan, Margaret C. Crofoot, Linda M. Fedigan, Claudia Fichtel, Lydia M. Hopper, Mary Catherine Mareno, Odile Petit, Anna Viktoria Schnoell, Eugenia Polizzi di Sorrentino, Bernard Thierry, Barbara Tiddi et al.

Scientific Reports 4, Article number: 7600 http://dx.doi.org/10.1038/srep07600

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Links that speak: The global language network and its association with global fame

People have long debated about the global influence of languages. The speculations that fuel this debate, however, rely on measures of language importance—such as income and population—that lack external validation as measures of a language’s global influence. Here we introduce a metric of a language’s global influence based on its position in the network connecting languages that are co-spoken. We show that the connectivity of a language in this network, after controlling for the number of speakers of a language and their income, remains a strong predictor of a language’s influence when validated against two independent measures of the cultural content produced by a language’s speakers.


Links that speak: The global language network and its association with global fame
Shahar Ronen, Bruno Gonçalves, Kevin Z. Hu, Alessandro Vespignani, Steven Pinker, and César A. Hidalgo

PNAS vol. 111 no. 52,  E5616–E5622, http://dx.doi.org/10.1073/pnas.1410931111

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Evolution of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity

The capacity to integrate information is a prominent feature of biological brains and has been related to cognitive flexibility as well as consciousness. To investigate how environment complexity affects the capacity for information integration, we simulated the evolution of artificial organisms (“animats”) controlled by small, adaptive neuron-like networks (“brains”). Task environments varied in difficulty due primarily to the requirements for internal memory. By applying measures of information integration, we show that, under constraints on the number of available internal elements, the animats evolved brains that were the more integrated the more internal memory was required to solve a given task. Thus, in complex environments with a premium on context-sensitivity and memory, integrated brain architectures have an evolutionary advantage over modular ones.


Albantakis L, Hintze A, Koch C, Adami C, Tononi G (2014) Evolution of Integrated Causal Structures in Animats Exposed to Environments of Increasing Complexity. PLoS Comput Biol 10(12): e1003966. http://dx.doi.org/10.1371/journal.pcbi.1003966 ;

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