Forum for the discussion of experiences in the representation and modeling of complex systems with highly non-linear behaviors / Foro para la discusión de temas relacionados con aspectos de la representacion de sistemas complejos y con comportamientos altamente no-lineales (Complex Adaptive Systems -CAS, System Dynamics, Agent Based Modeling)
"..donde una inteligencia global emerge de interacciones locales de seres individualmente no inteligentes."
-Sociobiology, O.E.Wilson-
La gran mayoria de lo que escribo en este blog es una compilacion del conocimiento en relacion a los sistemas complejos, a medida que lo voy descubriendo. Es un mundo de informacion teorica que deo explorar y de alguna manera ordenar a medida que vanzo por él, siendo mi meta final el obtener un doctorado en este tema. Es por tanto muy estimulante el encontrar evidencia de manifestaciones de hecho en el mundo natural, como la mostrada aqui, donde Conus Textile exhibe el patron descrito por los Algortitmos Calulares de Stephen Wolfram, que genera patrones de reglas locales simples, tal como el juego de la vida de Conway. La similitud para mi es impresionante.
Una simulacion de bandadas de pajaros muy influyente fue publicada por Craig Reynolds en 1987. Reynolds asumió que las bandadas de pajaros eran definidas por 3 fueras locales para su conformación: Evtar colisiones, ajustar velocidad y centrado en la bandada. Reynolds llamó a estos entes, “boids”, nombre dado por él a sus aves simuladas, y éstos:
1.- Cambian su direccion antes de colisionar entre ellos 2.- Tratan de avanzar a la misma velocidad que sus vecinos en la bandada 3.- Intentan moverse hacia el centro de la bandada como ellos la perciben
a traves de la implementacion de estas 3 reglas muy simples, los programas de Reynolds muestran un comportamiento de bandada muy realista, con clusters de boids danzando en un espacio tridimensional, partiendo la bandada alrededor de obstaculos, y juntándose nuevamente. Reynolds ha incluso generado la animacion de manadas y bandadas en peliculas, y su algoritmo simple pero no centralizado está detras de muchas animaciones, aplicacion conocida como Behavioral Animation (e.g. el Rey Leon de Disney)
Algunos software han sido desarrolados para explofrar este tipo de programacion, e incluso existen programas de codigo abierto (Opensource) disponibles, tal como Opensteer, un programa desarrollado por Craig Reynolds, y disponible para experimetar Online.
A traves de sistemas competitivos heterogeneso, asumiendo cooperacion interna y competencia No justa inter-sistema, este paper demuestra como la coevolucion de los parametros de este sistema (grado de competencia justa e injusta) depende de la provision externa de recursos. Este tipo de interaccion se encuentra en sistemas sociales, economicos, ecologicos y bioquimicos, y como un ejemplo, se considera el ejemplo de carteles vendedores de drogas.
El modelo consiste en una serie de unidades (individuos, maquinas, enzimas, etc.) agrupados en una serie de sistemas (organizaciones, fabricas, glyicosomas, etc.) cada uno compuesto por un numero fijo de unidades, y que pueden estar organizadas en tres configuraciones: 1.- Aislados (monomeros), 2.- Cooperando en parejas (dimeros), y 3.- Cooperando en grupos de a cuatro(tetrameros).
Las unidades involucradas en estas configuraciones cooperativas aumentan su habilidad al obtener recursos (clientes, materias primas, substarto, etc).
La disponibilidad de recursos puede ser alterada a traves de inhibidores. Cuando una unidad absorbe un inhibidor, su funcion se bloquea por un periodo de tiempo. Cuando la unidad pertenece a un dimero o tetramero, toda las otras unidades constituyentes tambien son bloqueadas como resultado de la absorcion de este inhibidor. Dos parametros caracterizan cada sistema: la fraccion de monomeros, y la produccion promedio de inhibidores por el sistema. Al usar algoritmos geneticos, observamos que la evolucion de los parametros del sistema mantiene sus valores promedio en el largo plazo para razones de abastecimiento latas y bajas, pero tiende a mostrar transiciones evolutivas globales cuando el abastecimiento de materias primas fluctua entre la abundancia y la escasez.
Festo's Bionic Learning Network has developed two colonies of bionic penguins that demonstrate collective behaviour. This type of behaviour - which psychologists also call crowd behaviour - refers to social processes which emerge in a spontaneous manner when members of a group interact. In robotic terms, each penguin is an autonomous self-regulating unit that is free to explore its defined environment using complex built-in navigation and communication facilities, and is capable of modifying its behaviour in the presence of others, to fulfil a group purpose.
Festo believes that autonomous, self-regulating processes are likely to become increasingly significant in automated production systems of the future. An example of this technology could be the organisation of highly flexible, autonomous robots within a pull-through production environment.
The transfer flow, from research to practical everyday use, is already apparent: the penguins use the highly innovative 3D Fin Ray Effect structure - co-developed with the specialist bionics company EvoLogics GmbH - to create very lifelike movement of their heads and tails. The 3D Fin Ray Effect structure is based on two flexible bands which meet at their tips to form a triangle, with interconnecting links spaced at regular intervals. Festo has incorporated this structure in an adaptive gripping device known as the FinGripper, manufactured from polyamide powder using a selective laser sintering process, which weighs just 10% of its equivalent metal counterpart and is capable of moving pressure-sensitive work-pieces of varying shapes and sizes very efficiently. To further demonstrate the potential benefits of this technology, Festo has taken its kinematic tripod robot solution and developed a dynamic display called BionicTripod, which integrates the gripper with an innovative 3-axis positioning system.
Festo is releasing two colonies of bionic penguins on the unsuspecting public, at the Hannover Messe trade exhibition in Germany. Each colony comprises three individuals. The AquaPenguins are confined to a water tank, and use special 3D sonar to swim around and explore their environment without bumping into one another. But the AirPenguins are a different matter altogether; perhaps because their real-life counterparts have evolved to the point where they are unable to fly like other marine birds, the bionic versions seem determined to make up for lost time. Although the air space available for these helium-filled creatures is loosely defined by ultrasonic transmitting stations, they are entirely free to move around their 'sea of air' without let or hindrance, using Xbee wireless links to communicate with each other.
This paper is concerned with complex macroscopic behaviour arising in many-body systems through the combinations of competitive interactions and disorder, even with simple ingredients at the microscopic level. It attempts to indicate and illustrate the richness that has arisen, in conceptual understanding, in methodology and in application, across a large range of scientific disciplines, together with a hint of some of the further opportunities that remain to be tapped. In doing so it takes the perspective of physics and tries to show, albeit rather briefly, how physics has contributed and been stimulated.
This video above is called The secret, social lives of bacteria, by a very dynamic speaking and brilliant molecular biologist named Bonnie Bassler of Princeton.
Unless you need to study about bacteria in some way, this 18 minute talk is pretty much all you need to know about bacteria and their impact on us. However, this is not just basic fundamental Bacteria 101. It also has cutting edge science put in such basic terms we could all understand it and be amazed. So even if you did study bacteria, there is likely something you can still learn from this talk. They need to show this video in any introductory class having anything to do with bacteria!
The amazing parts about this talk show a simple but potent system in the way bacteria strategically work together, and how we can use that system to negate their potential harm to us rather than killing them with antibiotics. Bacteria have to strategically work together because they are so small it is only together that they can have any impact on us. Their communications system is a simple but brilliant system of determining how many bacteria are in some locale, and bacteria of each types around them, and if that is sufficient numbers to do something. So much for having no brains! We have brains and yet we couldn’t hope to organize ourselves so effectively most of the time!
The language of bacteria is also discussed, and what’s shocking is the molecules they use to send out and receive to detect their numbers and identities all have a common root. No exceptions! It’s like our languages stemming from a common family! This discovery then allows us to create similar molecules to fool the bacteria into not doing what we don’t want them to, without killing them like antibiotics does. The reason for this is because antibiotics, in killing the bacteria, allows the ones that survive to mutate and become stronger. We are facing a huge antibiotic resistance from bacteria right now due to our overuse of antibiotics. If we keep this up, we will not win this war.
However, if we just fool the bacteria by running interference with their communication systems, to the point they never know there are enough of themselves to attack, they won’t mutate nearly as quickly. And we can do this specifically for all kinds of bacteria because their language molecules are very simple to determine.
This is a paper written by Peter Kropotkin in 1902, in the aftermath of the publication of Darwin's paper and within the context of the Russian revolution. Written partly in response to Social Darwinism and in particular to Thomas H. Huxley's Nineteenth Century essay, "The Struggle for Existence," Kropotkin's book drew on his experiences in scientific expeditions in Siberia to illustrate the phenomenon of cooperation. After examining the evidence of cooperation in nonhuman animals, "savages," "barbarians," in medieval cities, and in modern times, he concludes that cooperation and mutual aid are as important in the evolution of the species as competition and mutual strife , if not more so. Click here to read or dwonload this work.
Charles Darwin's theory of human evolution was published long before knowledge of genes was available. But Richard Dawkins reveals that an obscure letter found in a library proves Darwin was already doing research into heredity which anticipated the breakthroughs of the next century. Click here to read this article.
El pensamiento actual acerca de la biologia evolutiva mantiene que la competencia entre individuos es la clave para entender la seleccion natural. Cuando existe competencia, obviamente existe conflicto; la emergencia de la cooperacion sin embargo, es menos directa, i demanda un analisis mas en profundidad. Investigaciones se han enfocado en definir y expandir los modelos evolutivos de cooperación.
Mas aun, entender los mecanismos de la cooperación es relevante para otras áreas del conocimiento ademas de la biología. Antropología, economía, matemáticas, ciencia política, primatología y psicología están adoptando el enfoque de modelos evolutivos y desarrollando analogías basadas en este. Similarmente, biologos usan elementos de la teoria de juegos y analizan la cooperacion en "Juegos Evolutivos". No obtante esto, el intercambio entre investigadores de distintas areas, ha sido limitado. En busca de cerrar esta brecha, es que el Taller de Dahlem fue concebido.
Este libro, que nace de ese encuentro, abarca temas tales como las emociones en la cooperacion humana, reciprocidad, mercados biologicos, cooperacion y conflictos en multicelularidad, cooperacion genomica e intercelular, los origenes de la cooperacion humana, y la evolucion cultural de la cooperacion humana; el enfasis esta en la preguntas aun abiertas y las areas de investigacion futuras. Este libro es un gran aporte al creciente proceso de fertilizacion inter-disciplinaria sobre este tema.
Detalles Hardcover: 499 pages Publisher: The MIT Press; illustrated edition edition (November 1, 2003) Language: English ISBN-10: 0262083264 ISBN-13: 978-0262083263 Product Dimensions: 9 x 6.2 x 1.2 inches Link en Amazon.com
In these dark days, science brings a glimmer of hope: even in a world that rewards selfishness, cooperation can emerge and ultimately prevail. That world happens to be a computer simulation, but I'll take good news anywhere I can get it. "We report the sudden outbreak of predominant cooperation in a noisy world dominated by selfishness and defection," write Swiss Federal Institute of Technology sociologists Dirk Helbing and Wenjian Yu in a paper published Monday in the Proceedings of the National Academy of Sciences. Helbing specializes in complex simulations of crowd behavior, from fans in a soccer stadium to traffic jams. But like other crowd modelers, he's been stuck on a basic conundrum, known best from the Prisoner's Dilemma: if cooperative behavior potentially provides the highest rewards, but selfishness is the safest and most sensible course of action, how can cooperation emerge? The key, suggests Helbing's simulation, is mobility and imitation. When individuals are free to choose their associates and smart enough to imitate their success, cooperation emerges, then flourishes — and it doesn't take much to start the process. At each iteration in the simulation, just one in 20 units had a chance of abandoning selfishness, and the choice was usually punished. "After a very long time, there will be two or three or four individuals in the same neighborhood who just happen to cooperate, just by chance," said Helbing. "It's a happy coincidence — and once there's a sufficiently large cluster, cooperators do quite well. Defectors start to copy the behavior of cooperative clusters. And cooperation can persist and spread." In many ways, the Prisoner's Dilemma simulation is for game theorists what fruit flies are to biologists: a simple system in which basic principles can be uncovered, examined and hopefully extrapolated to people. It's just a model; a bit of mobility and imitation won't magically fix humanity's problems. But they might be important. "The sheer fact of moving from one place to another might have been an important precondition for the emergence and spreading of cooperation" in human cultural evolution, said Helbing. There might also be a lesson in Helbing's shifting red-and-blue dots for the cities of the future, where migratory populations often are often stuck in immigrant neighborhoods and denied social opportunities. "We face a huge amount of migration worldwide, and it's expected on an even larger scale in decades to come," he said. "According to experience, it takes one or two generations for newcomers and their families to integrate fully. That's a very long time. We have to have more efficient integration." Citation: "The outbreak of cooperation among success-driven individuals under noisy conditions." By Dirk Helbing and Wenjian Yu. Proceedings of the National Academy of Sciences, Vol. 106, No. 8, Feb. 23, 2009.
Phrases such as "survival of the fittest" and "every man for himself" may seem to accentuate the presence of political and social competition in American culture; however, there obviously are similar instances of inter- and intra-group conflict across almost all known organisms. So what makes competition so prevalent for life and why does it sometimes seem to be preferred over cooperation?
ScienceDaily (2009-04-07) -- One of the questions raised by evolutionary theory is how cooperative behavior, which benefits other members of a species at a cost to the individual, came to exist. If only the fittest survive, genes for a behavior that benefits everybody in a population should not last and cooperative behavior should die out. Now researchers have used game theory to understand one solution yeast use to get around this problem.
