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6 November, 2012 in Books, General, Images, People, Research, Videos | Tags: Agency, Altruism, biology, Collective Intelligence, collective phenomena, Complex Networks, Complex Systems, Evolution, heterophily, homophily, Human-Human interaction, Nicholas Christakis, Social Behaviour, Social cooperation, Social Networks, Society, Sociology, Stigmergy, Structure | 1 comment
Recent research have increasingly being focused on the relationship between Human-Human interaction, social networks (no, not the Facebook) and other Human-activity areas, like health. Nicholas Christakis (Harvard Univ. research link) points us that, people are inter-connected, and so as well, their health is inter-connected. This research engages two types of phenomena: the social, mathematical, and biological rules governing how social networks form (“Connection“) and the biological and social implications of how they operate to influence thoughts, feelings, and behaviours (“Contagion“), as in the self-organized stigmergy-like dynamics of Cognitive Collective Perception (link).
Above, Nicholas Christakis (in a 56m. documentary lecture produced by The Floating University, Sept. 2011) discusses the obvious tension and delicate balance between agency (one individual choices and actions) and structure (our collective responsibility), where here, structure refers not only to our co-evolving dynamic societal environment as well as to the permanent unfolding entangled nature of topological structure on complex networks, such as in human-human social networks, while asking: If you’re so free, why do you follow others? The documentary (YouTube link) resume states:
“If you think you’re in complete control of your destiny or even your own actions, you’re wrong. Every choice you make, every behaviour you exhibit, and even every desire you have finds its roots in the social universe. Nicholas Christakis explains why individual actions are inextricably linked to sociological pressures; whether you’re absorbing altruism performed by someone you’ll never meet or deciding to jump off the Golden Gate Bridge, collective phenomena affect every aspect of your life. By the end of the lecture Christakis has revealed a startling new way to understand the world that ranks sociology as one of the most vitally important social sciences.”
While cooperation is central to the success of human societies and is widespread, cooperation in itself, however, poses a challenge in both the social and biological sciences: How can this high level of cooperation be maintained in the face of possible exploitation? One answer involves networked interactions and population structure.
As perceived, the balance between homophily (where “birds of a feather flock together”) and heterophily (one where most of genotypes are negatively correlated), do requires further research. In fact, in humans, one of the most replicated findings in the social sciences is that people tend to associate with other people that they resemble, a process precisely known as homophily. As Christakis points out, although phenotypic resemblance between friends might partly reflect the operation of social influence, our genotypes are not materially susceptible to change. Therefore, genotypic resemblance could result only from a process of selection. Such genotypic selection might in turn take several forms. For short, let me stress you two examples. What follows are two papers, as well as a quick reference (image below) to a recent general-audience of his books:
1) Rewiring your network fosters cooperation:
“Human populations are both highly cooperative and highly organized. Human interactions are not random but rather are structured in social networks. Importantly, ties in these networks often are dynamic, changing in response to the behavior of one’s social partners. This dynamic structure permits an important form of conditional action that has been explored theoretically but has received little empirical attention: People can respond to the cooperation and defection of those around them by making or breaking network links. Here, we present experimental evidence of the power of using strategic link formation and dissolution, and the network modification it entails, to stabilize cooperation in sizable groups. Our experiments explore large-scale cooperation, where subjects’ cooperative actions are equally beneficial to all those with whom they interact. Consistent with previous research, we find that cooperation decays over time when social networks are shuffled randomly every round or are fixed across all rounds. We also find that, when networks are dynamic but are updated only infrequently, cooperation again fails. However, when subjects can update their network connections frequently, we see a qualitatively different outcome: Cooperation is maintained at a high level through network rewiring. Subjects preferentially break links with defectors and form new links with cooperators, creating an incentive to cooperate and leading to substantial changes in network structure. Our experiments confirm the predictions of a set of evolutionary game theoretic models and demonstrate the important role that dynamic social networks can play in supporting large-scale human cooperation.”, abstract in D.G. Rand, S. Arbesman, and N.A. Christakis, “Dynamic Social Networks Promote Cooperation in Experiments with Humans,” PNAS: Proceedings of the National Academy of Sciences (October 2011). [full PDF];
Picture – (book cover) Along with James Fowler, Christakis has authored also a general-audience book on social networks: Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives, 2011 (book link). For a recent book review, access here.
2) We are surrounded by a sea of our friends’ genes:
“It is well known that humans tend to associate with other humans who have similar characteristics, but it is unclear whether this tendency has consequences for the distribution of genotypes in a population. Although geneticists have shown that populations tend to stratify genetically, this process results from geographic sorting or assortative mating, and it is unknown whether genotypes may be correlated as a consequence of nonreproductive associations or other processes. Here, we study six available genotypes from the National Longitudinal Study of Adolescent Health to test for genetic similarity between friends. Maps of the friendship networks show clustering of genotypes and, after we apply strict controls for population strati!cation, the results show that one genotype is positively correlated (homophily) and one genotype is negatively correlated (heterophily). A replication study in an independent sample from the Framingham Heart Study veri!es that DRD2 exhibits signi!cant homophily and that CYP2A6 exhibits signi!cant heterophily. These unique results show that homophily and heterophily obtain on a genetic (indeed, an allelic) level, which has implications for the study of population genetics and social behavior. In particular, the results suggest that association tests should include friends’ genes and that theories of evolution should take into account the fact that humans might, in some sense, be metagenomic with respect to the humans around them.”, abstract in J.H. Fowler, J.E. Settle, and N.A. Christakis, “Correlated Genotypes in Friendship Networks,” PNAS: Proceedings of the National Academy of Sciences (January 2011). [full PDF].
19 March, 2012 in General, People, Videos | Tags: Cooperation, Cooperative Learning, Education, Educational system, Finland, Science, Social cooperation, Socialism, Society, Teachers, Technology, The Wealth of Nations | Leave a comment
Video – Finland’s educational system: Cenk Uygur and Ana Kasparian discuss the revolutionary educational system Finland has instituted and the results of that system on the education of their children. Read more about it at: Anu Partanen, “What Americans Keep Ignoring About Finland’s School Success“, The Atlantic magazine, US, Dec. 2011.
16 February, 2012 in General, Images, People | Tags: Altruism, Bounded Rationality, Cooperation, Game Theory, John Forbes Nash Jr, John Nash, Mathematics, Nash equilibrium, Prisoner's Dilemma, Social cooperation, Social Dilemmas, Social Norms | Leave a comment
[…] Nash: See if I derive an equilibrium (link) where prevalence is a non-singular event where nobody loses, can you imagine the effect that would have on conflict scenarios, arm negotiations… (…) currency exchange? […], in Memorable quotes for “A Beautiful Mind” (2001), movie directed by Ron Howard, starring Russell Crowe, along with Ed Harris.
26 October, 2011 in Books, General, People, Quotes | Tags: Altruism, Bounded Rationality, Complex Systems, Computer Simulation, Evolution, Evolutionary game dynamics, Game Theory, Martin Nowak, Prisoner's Dilemma, Social Behaviour, Social cooperation, Social Norms, Social Simulation, Trust | 3 comments
” […] What I refused to see is what the prisoner’s dilemma teaches: anyone who plays the “All Cooperate” strategy is a sucker, and incents the other to defect on every move. I now believe that the lesson of the prisoner’s dilemma is that a robust ethic succeeds where a weak one fails. Be fair, be strong, reward cooperation and punish defection, and you will have nothing to regret. […] “, in An Ethic Based on the Prisoner’s Dilemma, The Ethical Spectacle, September, 1995.
[…] Martin Nowak is known for his many influential papers on cooperation and in theoretical biology. This book is a popular writing on his scientific adventures, personal motivations and collaborations. Given his work it is remarkable is that this book does contain nor mathematical equations neither graphical illustrations. Nowak is currently a professor of mathematics and biology at Harvard University. Moreover, he directs since 2003 his own research program on Evolutionary Dynamics. This program has been made possible by a 30 million pledge by Wall Street tycoon Jeffrey Epstein. This is just one ingredient of the remarkable story of Nowak scientific life. The book starts with laying out the puzzle of cooperation illustrated by the prisoner’s dilemma. If both players are selfish and rational they will defect. Why do we see so much cooperation in human societies and other domains of the biological world? This puzzle was introduced to Nowak by Karl Sigmund, a professor in mathematics from the University of Vienna, while Nowak was a student in biochemistry. Sigmund talked about the famous Axelrod tournament and Nowak got hooked. The tournament of Axelrod assumed that the strategies did not make errors. What if there are errors? Will Tit for Tat still be a good strategy? His analysis showed that a more promising strategy is a more Win Stay, Loose Shift. This strategy leads to cooperation if both agents do the same, and defect if not. Hence agents can forgive.
The analysis of strategies that do well in direct reciprocity is one of the five chapters in which Nowak discuss five ways in which the prisoner’s dilemma can be solved. The second chapter is on indirect reciprocity. In a landmark paper with Karl Sigmund Nowak showed that when agents derive information on their reputation (image score) cooperation can evolve in one-shot prisoner’s dilemma. The third chapter is on spatial games and features another landmark paper on spatial chaos. This paper, written with Lord Robert May, shows that cooperation can evolve if agents interact with neighbours and imitate the best strategy of their neighbours. The forth chapter is on group selection. This controversial approach is now better known as multi-level selection. Finally, the fifth chapter is on kin-selection, the first theory on cooperation based on genetic relatedness. The discussion on the five ways to overcome the prisoner’s dilemma is especially interesting due to the discussion on the scientific process. How long hikes with Sigmund let to inspirations that let Nowak drop all other activities he was working on. How chance meetings let to new ideas. How he got, to Oxford, Princeton and finally Harvard.
In the second part of the book discusses cooperation in biology. It covers his applications to the origins of life, the study of cancer and the dominance of ant colonies. This work might be less familiar to the readers of JASSS. Especially the work on cancer, defectors in our own biology, can lead to practical applications. The final part of the book focuses on human societies. Humans are called supercooperators since they are the only organism that uses all five ways to solve social dilemmas. First the evolution of language is discussed. Nowak made important contributions to the study of language by simulating agents benefiting from mutual understanding in language games. According to Nowak, the emergence of language is the most important development in life since 600 million years. It resulted to new types of cooperation. Especially in the context of indirect reciprocity it is key to have language. We need gossip and other types of information transmission to derive reliable estimates on the reputation of strangers.
Then Nowak discusses public goods and the use of costly punishment to derive cooperation. This is the only part of the book where he discusses empirical research. With two graduate students he performed experiments which showed that punishment is not something special, but in line with earlier work on reciprocity and tit for tat. Then Nowak continues with his recent work on network theory and set theory. The book closes with a reflection on the consequences of his work. Cooperation is a crucial ingredient to evolution, but there always will be cycles. The question is how to re-establish cooperation after it has been collapsed. This book provides a nice overview of the findings of Nowak’s work. Note however, that Nowak has substantial work in other areas of research not discussed in the book such as infectious diseases. Together with science writer Roger Highfield, Nowak provides an inspirational story on science in practice. This covers the importance of his mentors in his early years, and his current role of a mentor to his students at Harvard. In conclusion, this is a marvellous book. Although I may not always agree with the findings of Nowak’s research, it is a motivating account on the messy practice of science. I highly recommend this book for students and faculty in social simulation and science in general. […], Reviewed by Marco A. Janssen
(Arizona State University) on JASSS 2011 [Nowak, Martin, Supercooperators: Altruism, Evolution, and Why We Need Each Other to Succeed, ISBN 9781439100189 (pb), Free Press (The): New York, NY, 2011].
27 May, 2010 in Books, General, Research | Tags: Altruism, Complex Systems, Computational Biology, Cooperation, Economy, Evolutionary game dynamics, Evolutionary game theory, Game Theory, Invisible Hand, Prisoner's Dilemma, Selfishness, Social cooperation, Social Dilemmas, Ultimatum games | Leave a comment
[…] Cooperation means that a donor pays a cost, c, for a recipient to get a benefit, b. In evolutionary biology, cost and benefit are measured in terms of fitness. While mutation and selection represent the main forces of evolutionary dynamics, cooperation is a fundamental principle that is required for every level of biological organization. Individual cells rely on cooperation among their components. Multicellular organisms exist because of cooperation among their cells. Social insects are masters of cooperation. Most aspects of human society are based on mechanisms that promote cooperation. Whenever evolution constructs something entirely new (such as multicellularity or human language), cooperation is needed. Evolutionary construction is based on cooperation. The five rules for cooperation which we examine in this chapter are: kin selection, direct reciprocity, indirect reciprocity, graph selection, and group selection. Each of these can promote cooperation if specific conditions are fulfilled. […], Martin A. Nowak, Karl Sigmund, How populations cohere: five rules for cooperation, in R. M. May and A. McLean (eds.) Theoretical Ecology: Principles and Applications, Oxford UP, Oxford (2007), 7-16. [PDF]
How does cooperation emerge among selfish individuals? When do people share resources, punish those they consider unfair, and engage in joint enterprises? These questions fascinate philosophers, biologists, and economists alike, for the “invisible hand” that should turn selfish efforts into public benefit is not always at work. The Calculus of Selfishness looks at social dilemmas where cooperative motivations are subverted and self-interest becomes self-defeating. Karl Sigmund, a pioneer in evolutionary game theory, uses simple and well-known game theory models to examine the foundations of collective action and the effects of reciprocity and reputation. Focusing on some of the best-known social and economic experiments, including games such as the Prisoner’s Dilemma, Trust, Ultimatum, Snowdrift, and Public Good, Sigmund explores the conditions leading to cooperative strategies. His approach is based on evolutionary game dynamics, applied to deterministic and probabilistic models of economic interactions. Exploring basic strategic interactions among individuals guided by self-interest and caught in social traps, The Calculus of Selfishness analyses to what extent one key facet of human nature–selfishness–can lead to cooperation. (from Princeton Press). [Karl Sigmund, The Calculus of Selfishness, Princeton Series on Theoretical and Computational Biology, Princeton University Press, ISBN: 978-1-4008-3225-5, 192 pp., 2009.]
What follows comes partly from chapter 1, available here:
THE SOCIAL ANIMAL: Aristotle classified humans as social animals, along with other species, such as ants and bees. Since then, countless authors have compared cities or states with bee hives and ant hills: for instance, Bernard de Mandeville, who published his The Fable of the Bees more than three hundred years ago. Today, we know that the parallels between human communities and insect states do not reach very far. The amazing degree of cooperation found among social insects is essentially due to the strong family ties within ant hills or bee hives. Humans, by contrast, often collaborate with non-related partners. Cooperation among close relatives is explained by kin selection. Genes for helping offspring are obviously favouring their own transmission. Genes for helping brothers and sisters can also favour their own transmission, not through direct descendants, but indirectly, through the siblings’ descendants: indeed, close relatives are highly likely to also carry these genes. In a bee hive, all workers are sisters and the queen is their mother. It may happen that the queen had several mates, and then the average relatedness is reduced; the theory of kin selection has its share of complex and controversial issues. But family ties go a long way to explain collaboration. The bee-hive can be viewed as a watered-down version of a multicellular organism. All the body cells of such an organism carry the same genes, but the body cells do not reproduce directly, any more than the sterile worker-bees do. The body cells collaborate to transmit copies of their genes through the germ cells – the eggs and sperm of their organism. Viewing human societies as multi-cellular organisms working to one purpose is misleading. Most humans tend to reproduce themselves. Plenty of collaboration takes place between non-relatives. And while we certainly have been selected for living in groups (our ancestors may have done so for thirty million years), our actions are not as coordinated as those of liver cells, nor as hard-wired as those of social insects. Human cooperation is frequently based on individual decisions guided by personal interests. Our communities are no super-organisms. Former Prime Minister Margaret Thatcher pithily claimed that “there is no such thing as society“. This can serve as the rallying cry of methodological individualism – a research program aiming to explain collective phenomena bottom-up, by the interactions of the individuals involved. The mathematical tool for this program is game theory. All “players” have their own aims. The resulting outcome can be vastly different from any of these aims, of course.
THE INVISIBLE HAND: If the end result depends on the decisions of several, possibly many individuals having distinct, possibly opposite interests, then all seems set to produce a cacophony of conflicts. In his Leviathan from 1651, Hobbes claimed that selfish urgings lead to “such a war as is every man against every man“. In the absence of a central authority suppressing these conflicts, human life is “solitary, poor, nasty, brutish, and short“. His French contemporary Pascal held an equally pessimistic view: : “We are born unfair; for everyone inclines towards himself…. The tendency towards oneself is the origin of every disorder in war, polity, economy etc“. Selfishness was depicted as the root of all evil. But one century later, Adam Smith offered another view.An invisible hand harmonizes the selfish efforts of individuals: by striving to maximize their own revenue, they maximize the total good. The selfish person works inadvertently for the public benefit. “By pursuing his own interest he frequently promotes that of the society more effectually than when he really intends to promote it“. Greed promotes behaviour beneficial to others. “It is not from the benevolence of the butcher, the brewer, or the baker, that we expect our dinner, but from their regard to their own self-interest. We address ourselves, not to their humanity but to their self-love, and never talk to them of our own necessities but of their advantages“. A similar view had been expressed, well before Adam Smith, by Voltaire in his Lettres philosophiques: “Assuredly, God could have created beings uniquely interested in the welfare of others. In that case, traders would have been to India by charity, and the mason would saw stones to please his neighbour. But God designed things otherwise….It is through our mutual needs that we are useful to the human species; this is the grounding of every trade; it is the eternal link between men“. Adam Smith (who knew Voltaire well) was not blind to the fact that the invisible hand is not always at work. He merely claimed that it frequently promotes the interest of the society, not that it always does. Today, we know that there are many situations – so-called social dilemmas – where the invisible hand fails to turn self-interest to everyone’s advantage.
9 May, 2010 in General, Images, Research | Tags: Co-Cognition, Co-Evolution, Collective Decision Support Systems, Collective Intelligence, Collective Perception, Complex Systems, Cooperation, David Hume, Game Theory, Jean Jacques Rousseau, John Nash, Nash equilibrium, Prisoner's Dilemma, Social cooperation | Leave a comment
“If you want to be incrementally better: Be competitive. If you want to be exponentially better: Be cooperative“. ~ Anonymous
Two hunters decide to spent their week-end together. But soon, a dilemma emerges between them. They could choose for hunting a deer stag together or either -individually- hunt a rabbit on their own. Chasing a deer, as we know, is something quite demanding, requiring absolute cooperation between them. In fact, both friends need to be focused for a long time and in position, while not being distracted and tempted by some arbitrary passing rabbits. On the other hand, stag hunt is increasingly more beneficiary for both, but that benefice comes with a cost: it requires a high level of trust between them. Somehow at some point, each hunter concerns that his partner may diverts while facing a tempting jumping rabbit, thus jeopardizing the possibility of hunting together the biggest prey.
The original story comes from Jean Jacques Rousseau, French philosopher (above). While, the dilemma is known in game theory has the “Stag Hunt Game” (Stag = adult deer). The dilemma could then take different quantifiable variations, assuming different values for R (Reward for cooperation), T (Temptation to defect), S (Sucker’s payoff) and P (Punishment for defection). However, in order to be at the right strategic Stag Hunt Game scenario we should assume R>T>P>S. A possible pay-off table matrix taking in account two choices C or D (C = Cooperation; D = Defection), would be:
Choice — C ——- D ——
C (R=3, R=3) (S=0, T=2)
D (T=2, S=0) (P=1, P=1)
Depending on how fitness is calculated, stag hunt games could also be part of a real Prisoner’s dilemma, or even Ultimatum games. As clear from above, highest pay-off comes from when both hunters decide to cooperate (CC). Over this case (first column – first row), both receive a reward of 3 points, that is, they both really focused on hunting a big deer while forgetting everything else, namely rabbits. However – and here is where exactly the dilemma appears -, both CC or DD are Nash equilibrium! That is, at this strategic landscape point no player has anything to gain by changing only his own strategy unilaterally. The dilemma appears recurrently in biology, animal-animal interaction, human behaviour, social cooperation, over Co-Evolution, in society in general, and so on. Philosopher David Hume provided also a series of examples that are stag hunts, from two individuals who must row a boat together up to two neighbours who wish to drain a meadow. Other stories exist with very interesting variations and outcomes. Who does not knows them?!
The day before last school classes, two kids decided to do something “cool”, while conjuring on appearing before their friends on the last school day period, both with mad and strange haircuts. Although, despite their team purpose, a long, anguish and stressful night full of indecisiveness followed for both of them…