This video shows six laboratory demonstrations of chaos andnonlinear phenomena, intended for use in a first course on nonlineardynamics. Steven Strogatz explains the principles being illustrated andwhy they are important.
Research in Complex Social Systems needs an integrative approach from Engineering, Social Sciences and Management. Agent Based Modelling and Agent Based Social Simulation provide the framework we have adopted to deal with complex systems. Our main interests are:
Industrial organization: the study of strategic interactions of competing/cooperating firms or agents in different market and regulatory frameworks. This line can provide decision support on issues such as pricing, advertisement, product lines, target quality, response to competitors, alliances or market regulation. These studies are often carried out combining (agent-based) simulation with (evolutionary) game theory and network theory.Enterprise Complex Systems: Governance. Learning and organizational changePolicy Rehearsal and Industry Dynamics.Artificial Economics: Market institutions. Auctions.Artificial intelligence: learning algorithms.
Agent Based Modelling and Agent Based Simulation
Agent based simulations provide a new and exciting avenue. Researches and advisers can compare and explore alternative scenarios and institutional arrangements to evaluate the consequences of policy actions in terms of economic, social and ecological impacts. But as a new field it demands from the modellers a great deal of creativeness, expertise and "wise choice".
Agent based modelling allows us to study the interactions between the individuals and the institutions. The simulation is focused in the dynamics of the processes, more than in the existence of equilibrium. Out of equilibrium dynamics are far more interesting than static equilibrium into which the system could be finally absorbed. Transients are no more difficult to study than equilibria. Agent-agent and agent-environment interactions are at the core of the approach according to simple local rules, dispensing of ex-ante "super-agents" to assure the emergence of equilibrium patterns. Space is distinct from the agent population in contrast with the differential equation models. The agents are heterogeneous and truly individualistic, whereas in mechanistic models one has to assume group behaviour to make the models analytically tractable. They compete in rigour with mechanistic modelling. If the programme is based upon production rules, it will be as internally consistent as it is the logic used. If it is not, it can be checked for internal consistency, before feeding it with the actual model.
Un emergente Centro de Investigación, cuyo objetivo principal es la introducción de modernos métodos matemáticos y computacionales de los sistemas complejos, aplicados a la solución de problemas de salud, utilizando las nuevas tecnologías de la informática y las comunicaciones y propiciando la integración inter y transdisciplinar con profesionales de diversas áreas del conocimiento, en proyectos de investigación dentro del Sistema Nacional de Ciencia e Innovación Tecnológica.
The New England Complex Systems Institute (NECSI) is an independent academic research and educational institution with students, postdoctoral fellows and faculty. In addition to the in-house research team, NECSI has co-faculty, students and affiliates from MIT, Harvard, Brandeis and other universities nationally and internationally.
Face-to-face contacts between individuals contribute to shape social networks and play an important role in determining how infectious diseases can spread within a population. It is thus important to obtain accurate and reliable descriptions of human contact patterns occurring in various day-to-day life contexts. Recent technological advances and the development of wearable sensors able to sense proximity patterns have made it possible to gather data giving access to time-varying contact networks of individuals in specific environments. Here we present and analyze two such data sets describing with high temporal resolution the contact patterns of students in a high school. We define contact matrices describing the contact patterns between students of different classes and show the importance of the class structure. We take advantage of the fact that the two data sets were collected in the same setting during several days in two successive years to perform a longitudinal analysis on two very different timescales. We show the high stability of the contact patterns across days and across years: the statistical distributions of numbers and durations of contacts are the same in different periods, and we observe a very high similarity of the contact matrices measured in different days or different years. The rate of change of the contacts of each individual from one day to the next is also similar in different years. We discuss the interest of the present analysis and data sets for various fields, including in social sciences in order to better understand and model human behavior and interactions in different contexts, and in epidemiology in order to inform models describing the spread of infectious diseases and design targeted containment strategies.
This is the first in a series of articles recounting the history of the Santa Fe Institute drawn from primary and, in a few cases, secondary sources.
By John German
In George Cowan's telling, the notion for a Santa Fe Institute began to form in the summer of 1956. He had been invited to the Aspen Institute, where prominent intellectuals from the arts, science, and culture gathered for free-form philosophical exchanges. He had just participated as the lone scientist in a discussion of literature. (...)
IXXI is not a lab, but a light structure that favors interdisciplinary research to model complex sytems such as biological or social systems, technological networks…
IXXI uses four steps to help creating interdisciplinary teams :
Animation of the community through workshops, seminar, IXXI-days to promote discussions between disciplinesSupport emergent projects : two calls per year (spring – falls). This is an easy (but small) financing to support emergent projects/events without disciplinary barriersHosting researchers that are at the heart of the community through their scientific fields. Presently, we host D-NET team from Computer Science Lab at ENS de Lyon, who focuses on the dynamics of social and medical networks, members of the European project DYNANETS and the COSMO start-up (links to be added).Teaching : IXXI has created a Master (2nd year) on “modeling of complex systems”, which is a common option for students in Masters of mathematics, computer science, physics and biology.
RA-S organizes sessions at the annual EAEPE conferences and provides the opportunity for researchers working on/with evolutionary computational simulations to meet and exchange ideas. Special attention is given to interdisciplinary approaches addressing the evolution of economic agents and institutions in non-equilibrium processes under bounded rationality and social learning. In particular, we look for contributions offering new insights to collective action problems in the context of the long-run sustainability and interactions between nature, society and economy. Through the use of approaches from evolutionary economics and complex adaptive systems, we want to shed light on problems such as:
evolutionary macroeconomics: investment-finance interlinkages, endogenous business cycles, bubbles and crashes;societal evolution: individual and social choices, governance, evolution of cooperation, institutional emergence and durability;culture-environment co-evolution: consumption dynamics, technology transition, sustainability.
Of course, we are also happy to discuss the development of the method as such in a critical way.
Noviembre 04, 2013 - Noviembre 06, 2013 (Todo el día)
El Centro de Ciencias de la Complejidad (C3) tiene el placer de organizar un evento para un amplio público con ponentes invitados nacionales e internacionales con el objetivo de mostrar los beneficios que el enfoque de la complejidad ha logrado en diversas áreas, incluyendo sistemas biológicos, sociales, culturales y tecnológicos. Durante el evento también se presentarán los distintos programas de investigación que se están desarrollando en el C3 y el proyecto del nuevo edificio del C3 en Ciudad Universitaria. Con este simposio se invita a la comunidad universitaria a participar y colaborar en el desarrollo de proyectos y la resolución de problemas en campos múltiples usando las herramientas que ofrecen las ciencias de la complejidad.
Lugar: Auditorio Alfonso Caso Ciudad Universitaria, México D.F.
The National Autonomous University of Mexico (UNAM) has an open call for postdoctoral fellowships to start in March, 2014 (with a close deadline!). Candidates should have obtained a PhD degree within the last three years and be under 36 years, both to the date of the beginning of the fellowship. The area of interests of candidates should fall within complex systems, artificial life, information, evolution, cognition, robotics, and/or philosophy.
The ICREA-Complex Systems Lab, part of the Biology Department ofUniversitat Pompeu Fabra/ PRBB and member of the Institut de Biologia Evolutiva. We are an interdisciplinary team exploring the evolution of complex systems, both natural and artificial, searching for their common laws of organization. We do both theoretical and experimental work, closely working in collaboration with the Santa Fe Institute. Our research spans a broad range of areas, including statistical physics of complex sytems,artificial life, biological computation, synthetic, systems and network biology.
"The ISC-PIF (Institut des Systèmes Complexes, Paris Île-de-France – Paris Île-de-France Complex Systems Institute) is a multidisciplinary research and training center which promotes the development of French, European and international strategic projects on complex adaptive systems."
The Center for the Study of Complex Systems (CSCS) is a broadly interdisciplinary program in the College of Literature, Science and the Arts (LSA) at the University of Michigan in Ann Arbor, Michigan. Our mission is to encourage and facilitate research and education in the general area of nonlinear, dynamical and adaptive systems.