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Santa Fe Institute

NonprofitSanta Fe, New Mexico, United States
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 & Complex network. The organization has 558 authors who have published 4558 publications receiving 396015 citations. The organization is also known as: SFI.


Papers
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Journal ArticleDOI
TL;DR: In this paper, a simple evolutionary process can discover sophisticated methods for emergent information processing in decentralized spatially extended systems, and the mechanisms underlying the resulting emergent computation are explicated by a technique for analyzing particle-based logic embedded in pattern-forming systems.
Abstract: A simple evolutionary process can discover sophisticated methods for emergent information processing in decentralized spatially extended systems. The mechanisms underlying the resulting emergent computation are explicated by a technique for analyzing particle-based logic embedded in pattern-forming systems. Understanding how globally coordinated computation can emerge in evolution is relevant both for the scientific understanding of natural information processing and for engineering new forms of parallel computing systems.

251 citations

Journal ArticleDOI
TL;DR: In this article, the authors survey the literature on the economic consequences of the structure of social networks and develop a taxonomy of macro and micro characteristics of social-interaction networks and discuss both the theoretical and empirical findings concerning the role of those characteristics in determining learning, diffusion, decisions, and resulting behaviors.
Abstract: We survey the literature on the economic consequences of the structure of social networks. We develop a taxonomy of "macro" and "micro" characteristics of social-interaction networks and discuss both the theoretical and empirical findings concerning the role of those characteristics in determining learning, diffusion, decisions, and resulting behaviors. We also discuss the challenges of accounting for the endogeneity of networks in assessing the relationship between the patterns of interactions and behaviors.

250 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a systematic effort to answer the question, What are archaeology's most important scientific challenges? Starting with a crowd-sourced query directed broadly to the professional community of archaeologists, the authors augmented, prioritized, and refined the responses during a two-day workshop focused specifically on this question.
Abstract: This article represents a systematic effort to answer the question, What are archaeology’s most important scientific challenges? Starting with a crowd-sourced query directed broadly to the professional community of archaeologists, the authors augmented, prioritized, and refined the responses during a two-day workshop focused specifically on this question. The resulting 25 “grand challenges” focus on dynamic cultural processes and the operation of coupled human and natural systems. We organize these challenges into five topics: (1) emergence, communities, and complexity; (2) resilience, persistence, transformation, and collapse; (3) movement, mobility, and migration; (4) cognition, behavior, and identity; and (5) human-environment interactions. A discussion and a brief list of references accompany each question. An important goal in identifying these challenges is to inform decisions on infrastructure investments for archaeology. Our premise is that the highest priority investments should enable us to address the most important questions. Addressing many of these challenges will require both sophisticated modeling and large-scale synthetic research that are only now becoming possible. Although new archaeological fieldwork will be essential, the greatest pay off will derive from investments that provide sophisticated research access to the explosion in systematically collected archaeological data that has occurred over the last several decades.

250 citations

Journal ArticleDOI
TL;DR: In this paper, the authors investigate the contribution of within-group cultural affinity to the ability of parochial groups to cooperate in social dilemmas, in which the losses incurred by not trading with outsiders are offset by an enhanced ability to enforce informal contracts by fostering trust among insiders.
Abstract: Decentralized groups such as close knit residential neighborhoods and ethnically linked businesses often achieve high levels of cooperation while engaging in exclusionary practices that we call parochialism. We investigate the contribution of within-group cultural affinity to the ability of parochial groups to cooperate in social dilemmas. We analyze parochial networks in which the losses incurred by not trading with outsiders are offset by an enhanced ability to enforce informal contracts by fostering trust among insiders. We show that there is a range of degrees of parochialism for which parochial networks can coexist with an anonymous market offering unrestricted trading opportunities.

250 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide an analysis of the asymptotic properties of Pareto optimal consumption allocations in a stochastic general equilibrium model with heterogeneous consumers and investigate the market selection hypothesis that markets favor traders with more accurate beliefs.
Abstract: This paper provides an analysis of the asymptotic properties of Pareto optimal consumption allocations in a stochastic general equilibrium model with heterogeneous consumers. In particular, we investigate the market selection hypothesis that markets favor traders with more accurate beliefs. We show that in any Pareto-optimal allocation whether each consumer vanishes or survives is determined entirely by discount factors and beliefs. Whereas equilibrium allocations in economies with complete markets are Pareto optimal, our results characterize the limit behavior of these economies. We show that, all else equal, the market selects for consumers who use Bayesian learning with the truth in the support of their prior and selects among Bayesians according to the size of their parameter space. Finally, we show that in economies with incomplete markets, these conclusions may not hold. With incomplete markets, payoff functions can matter for long-run survival, and the market selection hypothesis fails.

249 citations


Authors

Showing all 606 results

NameH-indexPapersCitations
James Hone127637108193
James H. Brown12542372040
Alan S. Perelson11863266767
Mark Newman117348168598
Bette T. Korber11739249526
Marten Scheffer11135073789
Peter F. Stadler10390156813
Sanjay Jain10388146880
Henrik Jeldtoft Jensen102128648138
Dirk Helbing10164256810
Oliver G. Pybus10044745313
Andrew P. Dobson9832244211
Carel P. van Schaik9432926908
Seth Lloyd9249050159
Andrew W. Lo8537851440
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202341
202241
2021297
2020309
2019263
2018231