Santa Fe Institute

About: Santa Fe Institute is a nonprofit organization based out in Santa Fe, New Mexico, United States. It is known for research contribution in the topics: Population & Context (language use). The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.

The small world of human language

Abstract: Words in human language interact in sentences in non-random ways, and allow humans to construct an astronomic variety of sentences from a limited number of discrete units. This construction process is extremely fast and robust. The co-occurrence of words in sentences reflects language organization in a subtle manner that can be described in terms of a graph of word interactions. Here, we show that such graphs display two important features recently found in a disparate number of complex systems. (i) The so called small-world effect. In particular, the average distance between two words, d (i.e. the average minimum number of links to be crossed from an arbitrary word to another), is shown to be d approximately equal to 2-3, even though the human brain can store many thousands. (ii) A scale-free distribution of degrees. The known pronounced effects of disconnecting the most connected vertices in such networks can be identified in some language disorders. These observations indicate some unexpected features of language organization that might reflect the evolutionary and social history of lexicons and the origins of their flexibility and combinatorial nature.

A general model for ontogenetic growth

Abstract: Several equations have been proposed to describe ontogenetic growth trajectories for organisms justified primarily on the goodness of fit rather than on any biological mechanism. Here, we derive a general quantitative model based on fundamental principles for the allocation of metabolic energy between maintenance of existing tissue and the production of new biomass. We thus predict the parameters governing growth curves from basic cellular properties and derive a single parameterless universal curve that describes the growth of many diverse species. The model provides the basis for deriving allometric relationships for growth rates and the timing of life history events.

Identity and Search in Social Networks

Abstract: Social networks have the surprising property of being "searchable": Ordinary people are capable of directing messages through their network of acquaintances to reach a specific but distant target person in only a few steps. We present a model that offers an explanation of social network searchability in terms of recognizable personal identities: sets of characteristics measured along a number of social dimensions. Our model defines a class of searchable networks and a method for searching them that may be applicable to many network search problems, including the location of data files in peer-to-peer networks, pages on the World Wide Web, and information in distributed databases.

The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective

Abstract: One of the most influential ideas in the past 30 years is the Efficient Markets Hypothesis, the idea that market prices incorporate all information rationally and instantaneously. However, the emerging discipline of behavioral economics and finance has challenged this hypothesis, arguing that markets are not rational, but are driven by fear and greed instead. Recent research in the cognitive neurosciences suggests that these two perspectives are opposite sides of the same coin. In this article I propose a new framework that reconciles market efficiency with behavioral alternatives by applying the principles of evolution - competition, adaptation, and natural selection - to financial interactions. By extending Herbert Simon's notion of "satisficing" with evolutionary dynamics, I argue that much of what behavioralists cite as counterexamples to economic rationality - loss aversion, overconfidence, overreaction, mental accounting, and other behavioral biases - are, in fact, consistent with an evolutionary model of individuals adapting to a changing environment via simple heuristics. Despite the qualitative nature of this new paradigm, the Adaptive Markets Hypothesis offers a number of surprisingly concrete implications for the practice of portfolio management.

Growing Artificial Societies: Social Science from the Bottom Up

Abstract: Part I Introduction: "Artificial Society" models life and death on the sugarscape sex, culture and conflict - the emergence of history sugar and spice - trade comes to the sugarscape disease agents a society is born artificial societies versus traditional models artificial societies versus a life toward generative social science - can you grow it?. Part II Life and death on the sugarscape: in the beginning - there was sugar the agents artificial society on the sugarscape wealth and its distribution in the agent population social networks of neighbours migration summary. Part III Sex, culture and conflict - the emergence of history: sexual reproduction cultural processes combat the proto-history. Part IV Sugar and spice - trade comes to the sugarscape: spice - a second commodity trade rules markets of bilateral traders emergent economic networks social computation, emergent computation summary and conclusions. Part V Disease processes: models of disease transmission and immune response immune system response disease transmission digital diseases on the sugarscape disease transmission networks. Part VI Conclusions: summary some extensions of the current model other artificial societies formal analysis of artificial societies generative social science looking ahead. Appendices: software engineering aspects of artificial societies summary of rule notation state-dependence on the welfare function.