scispace - formally typeset
Search or ask a question
Institution

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
More filters
BookDOI
Samuel Bowles1
31 Dec 2003
TL;DR: The authors introduced modern microeconomic theory and developed a theory of how economic institutions shape individual behavior, and how institutions evolve due to individual actions, technological change, and chance events using evolutionary game theory, contract theory, behavioral experiments, and the modeling of dynamic processes.
Abstract: In this novel introduction to modern microeconomic theory, Samuel Bowles returns to the classical economists' interest in the wealth and poverty of nations and people, the workings of the institutions of capitalist economies, and the coevolution of individual preferences and the structures of markets, firms, and other institutions. Using recent advances in evolutionary game theory, contract theory, behavioral experiments, and the modeling of dynamic processes, he develops a theory of how economic institutions shape individual behavior, and how institutions evolve due to individual actions, technological change, and chance events. Topics addressed include institutional innovation, social preferences, nonmarket social interactions, social capital, equilibrium unemployment, credit constraints, economic power, generalized increasing returns, disequilibrium outcomes, and path dependency.Each chapter is introduced by empirical puzzles or historical episodes illuminated by the modeling that follows, and the book closes with sets of problems to be solved by readers seeking to improve their mathematical modeling skills. Complementing standard mathematical analysis are agent-based computer simulations of complex evolving systems that are available online so that readers can experiment with the models. Bowles concludes with the time-honored challenge of "getting the rules right," providing an evaluation of markets, states, and communities as contrasting and yet sometimes synergistic structures of governance. Must reading for students and scholars not only in economics but across the behavioral sciences, this engagingly written and compelling exposition of the new microeconomics moves the field beyond the conventional models of prices and markets toward a more accurate and policy-relevant portrayal of human social behavior.

935 citations

Book ChapterDOI
TL;DR: In this paper, the authors propose a theory of asset pricing based on heterogeneous agents who continually adapt their expectations to the market that these expectations aggregatively create, and explore the implications of this theory computationally using Santa Fe artificial stock market.
Abstract: This chapter proposes a theory of asset pricing based on heterogeneous agents who continually adapt their expectations to the market that these expectations aggregatively create. It explores the implications of this theory computationally using Santa Fe artificial stock market. Computer experiments with this endogenous-expectations market explain one of the more striking puzzles in finance: that market traders often believe in such concepts as technical trading, "market psychology," and bandwagon effects, while academic theorists believe in market efficiency and a lack of speculative opportunities. Academic theorists and market traders tend to view financial markets in strikingly different ways. Standard (efficient-market) financial theory assumes identical investors who share rational expectations of an asset's future price, and who instantaneously and rationally discount all market information into this price. While a few academics would be willing to assert that the market has a personality or experiences moods, the standard economic view has in recent years begun to change.

929 citations

Journal ArticleDOI
TL;DR: The results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus, and a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools is proposed.
Abstract: Assessing the effectiveness of non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-CoV-2 is critical to inform future preparedness response plans. Here we quantify the impact of 6,068 hierarchically coded NPIs implemented in 79 territories on the effective reproduction number, Rt, of COVID-19. We propose a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools. We validate our findings with two external datasets recording 42,151 additional NPIs from 226 countries. Our results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus. Less disruptive and costly NPIs can be as effective as more intrusive, drastic, ones (for example, a national lockdown). Using country-specific ‘what-if’ scenarios, we assess how the effectiveness of NPIs depends on the local context such as timing of their adoption, opening the way for forecasting the effectiveness of future interventions. Analysing over 50,000 government interventions in more than 200 countries, Haug et al. find that combinations of softer measures, such as risk communication or those increasing healthcare capacity, can be almost as effective as disruptive lockdowns.

927 citations

Journal ArticleDOI
06 Jul 2000-Nature
TL;DR: Research in social insect behaviour has provided computer scientists with powerful methods for designing distributed control and optimization algorithms that tend to exhibit a high degree of flexibility and robustness in a dynamic environment.
Abstract: Research in social insect behaviour has provided computer scientists with powerful methods for designing distributed control and optimization algorithms. These techniques are being applied successfully to a variety of scientific and engineering problems. In addition to achieving good performance on a wide spectrum of 'static' problems, such techniques tend to exhibit a high degree of flexibility and robustness in a dynamic environment.

923 citations

Journal ArticleDOI
TL;DR: It is argued that the agent-based computational model permits a distinctive approach to social science for which the term “generative” is suitable, and the connection between agent- based modeling and classical emergentism is taken up, criticizing the latter and arguing that the two are incompatible.
Abstract: This article argues that the agent-based computational model permits a distinctive approach to social science for which the term “generative” is suitable. In defending this terminology, features distinguishing the approach from both “inductive” and “deductive” science are given. Then, the following specific contributions to social science are discussed: The agent-based computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist phenomena in social science. Agent-based modeling provides a powerful way to address certain enduring—and especially interdisciplinary—questions. It allows one to subject certain core theories—such as neoclassical microeconomics—to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise—or “map up”—to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agent-based (“bottom up”) models. The agent-based approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agent-based modeling offers powerful new forms of hybrid theoretical-computational work; these are particularly relevant to the study of non-equilibrium systems. The agentbased approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science—some related to intractability, and some to undecidability proper. Finally, since “emergence” figures prominently in this literature, I take up the connection between agent-based modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible. ! 1999 John Wiley & Sons, Inc.

912 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
Network Information
Related Institutions (5)
Massachusetts Institute of Technology
268K papers, 18.2M citations

90% related

University of Oxford
258.1K papers, 12.9M citations

90% related

Princeton University
146.7K papers, 9.1M citations

89% related

Max Planck Society
406.2K papers, 19.5M citations

89% related

University of California, Berkeley
265.6K papers, 16.8M citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202341
202241
2021297
2020309
2019263
2018231