CSSS 2009 Santa Fe-Final Papers

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CSSS Santa Fe 2009


Innovation, Sustainability and Growth of Human Social Organizations from Cities to Corporations

Summary: The intent of this research is to build on the successful body of work that has already begun at SFI on developing a broad fundamental, quantitative, predictive theory of social organizations. A major component is to understand the role of innovation and adaptability in shaping the growth and sustainability of cities to corporations. Such a theoretical framework is potentially very powerful for a company like Boeing in helping to recognize and understand that its growth, evolution and development have been constrained by general "laws" which may have important implications for its long-term survivability. Such laws reflect the general dynamical and structural properties of the multiple underlying networks of the organization itself as well as its relationship with the broader business community. This is manifested in generic scaling laws that indicate that organizations that participate in a business/economic ecology did not evolve, grow and adapt either "randomly" or in a planned controlled manner but were subject to dynamical laws. From a research perspective we view Boeing as a "case study" by providing data and significant support for the research. The project will be focused on understanding these big questions by seeking to reveal the underlying principles, constraints and dynamics independent of the details by which companies grow and evolve driven by innovation (their "coarse-grained behavior").

By Michael Richey, Geoffrey West, Luis Bettencourt, Jessika Trancik

The Effect of Gossip on Social Networks

Summary: In this project we look at the effects of the spread of gossip (defined as information passed between two individuals A and B about an individual C who is not present) on social network structure.

By (Group Page): Allison Shaw, Chang Yu, David Brooks, Milena Tsvetkova, Roozbeh Daneshvar

Deconstructing CSSS09 Social Network

Summary: We present a social network analysis of the Santa Fe Institute Complex Systems Summer School (CSSS) 2009. CSSS 2009 participants consisted of complex systems researchers who were competitively selected to attend the month-long program. The international and interdisciplinary group spent four weeks together attending lectures, engaging in discussions, and collaborating on projects related to complex systems. We collected network data at three different time points during the program to observe the evolution of the CSSS 2009 network structure. Our results suggest that: 1) The CSSS 2009 network was fluid: it appears that links could form and break quickly; 2) The network was relatively decentralized; 3) The network had relatively low average distance, low compactness, and high breadth; 4) The network was sparser in the middle of the program than at the beginning or at the end; 4) In general, CSSS 2009 participants appear to have mixed well; 5) Similarities in areas of study, however, appear to have influenced the formation of new links as well as the maintenance of potential long-term links.

By (Group Page): Margreth Keiler, Murad Mithani, Roozbeh Daneshvar, Wendy Ham

The Effect of Disaggregation on Infection Spreading in a social network: 'More' may not be 'Merrier'

Summary: This project analyzes the dynamics of infection spreading in the disaggregated framework of a social network using prevalence data for different countries.

By: Varsha Kulkarni

Mom made me do it: Division of labor via maternal effects

Summary: We explore an alternative to cooperation for the evolution of division of labor (maternal manipulation) by means of an individual-based model.

By: Mauricio Gonzalez-Forero, Mareen Hofmann

Foraging on the Move

Summary:In this project we develop a model for organisms that forage in groups while migrating (e.g. caribou, wildebeest), to understand how individuals should balance foraging and flocking behaviors.

By (Group Page): Allison Shaw, Andrew Berdahl, Kate Behrman, Liliana Salvador, Steven Lade

Approaches to Panarchy

Summary: Panarchy refers to a nested set of interacting dynamical systems, each one cycling over a hierarchy of scales in time and space. This concept provides a framework for thinking about complex systems in ecology, economics, sociology, etc. We consider novel examples and applications of panarchy.

By: Barbara Bauer, Andrew Noble, Damian Winters

Spiking Neural Networks on the Cusp of Chaos: Initial Report

Summary: Spiking neural networks, even of small order, show great variability in their behavioral patterns. This paper is an initial look at how structure of small spiking networks influence their measured behavior over time. Of particular interest are networks showing non-periodic behavior, one of the tell-tale indicators of chaos in the underlying dynamics.

By: R. Watson

Terrorism: Radicalization Mechanism and Spread Control

Summary: Preventing the spread of radical ideologies requires models capable of identifying areas and agents before occurrence of terrorist act. We develop a model that captures a radicalization mechanism through several intermediate stages of individuals. We show how our model can combat the development of terrorist networks even with limited information on a target terrorist network.

By(Group page): Alhaji Cherif, Hirotoshi Yoshioka, Wei Ni, Prasanta Bose

Acupuncture Points Complex Networks in Human Body

Summary: The therapeutic properties of the points of the fourteen meridians are generalized on the basis of the meridian is amenable to treatment. We constructed an acupuncture complex network of a portion of the body depending on different kinds of illness to figure out interactions between acupuncture points. We use 44 common illnesses such as common cold, headache as the portion to do the research. The constructed network contains a large component of 70 nodes out of 770 acupuncture points around the body.

By : Guimei Zhu, Dave Brooks, Brian Hollar,

The Roundtable - An Agent-Based Model of Conversation Dynamics

Abstract. We present and analyze an agent-based model of conversation dynamics. The model develops from intuitive assumptions derived from experimental evidence, it abstracts from conversation content and semantics while including topological and psychological information, and is driven by stochastic dynamics. The model exhibits rich behavior and can capture many aspects of real-life conversations. Its potential generalizations, including individual preferences, memory effects and more complex topologies, may find useful applications in other fields of research where dynamically-interacting and networked agents play a fundamental role.

By Lucas Lacasa, Massimo Mastrangeli and Martin Schmidt

Exploring source-sink dynamics of pre-vaccination measles epidemics using a spectral formulation of Granger causality

We present a method for determining spatial contact networks from time series data of disease transmission.

By Kathrine Behrman, Alexander Mikheyev and Erin Taylor

Computational investigation of dynamic response of small networks: a research proposal

Abstract We propose to determine the reaction of every network of 3-5 nodes to a standardised signal. We see the networks as cellular signalling modules, but other interpretations may apply as well. We argue that the results of this project may shed light on evolutionary properties of small molecular networks. The computational framework we propose to use is probabilistic model checking, which guarantees a mathematically sound and completely automatic classification of responses. We invite the reader to undertake the research, with our assistance if required.

By Rosemary Braun, Marek Kwiatkowski and Alexander Mikheyev

Scalable Efficient Agent Based Models

Abstract Agent based models (ABMs) are characterized by purposive intelligent agents which interact to yield complex emergent behaviors. While each agent operates with an autonomous localized set of rules, these rules typically involve interactions among agents and with the agents’ environment, presenting challenges when attempting to simulate very large populations of agents. At the same time, the scaling properties of complex adaptive systems are such that it is important to study the properties of an ABM over wide ranges of population size. This is because the emergent properties of a system typically change with scope and scale: mammalian basal metabolic rate scales sublinearly with animal mass, and incidence of crime in a city scales superlinearly with city population size. The attached Abstract of Work in Progress describes work conducted heretofore in deploying a spatial ABM to a distributed-memory computational cluster, along with planned next steps.

By Matt McMahon

1,2,3, language! Building the phylogenetric tree of languages with numbers

Abstract In this paper we make use of bioinformatics tools to build up the phylogenetic tree of languages. We had access to a large dataset gathering the numbers one to ten in over five thousand languages. In a first step, for each language we have concatenated each of the ten numbers in a string. After defining a mapping between the 26-letter alphabet and the DNA-like codons, we make use of a global alignment method to calculate the distance between pairs of strings, i.e. between languages. We finally generate the distance matrix and its associated phylogenetic tree. Specifically, we have used this method to generate the phylogenetic tree of indoeuropean languages. Despite the small size of the dataset (only ten words per language), preliminary results perfectly match the state of the art. We finally discuss some potential applications and future work, on relation to culture-based concepts such as trading or spreading of culture.

By Andrew Berdahl and Lucas Lacasa

Crossover phenomenon in the performance of an Internet search engine

Abstract In this work we explore the ability of Google search engine to find results for random N-letter strings. These random strings, dense over the set of possible N-letter words, address the existence of typos, acronyms, and other words without semantic meaning. Interestingly, we find that the probability of finding such strings sharply drops from one to zero at Nc = 6. The behavior of such order parameter suggests the presence of a transition-like phenomenon in the geometry of the search space. Furthermore, we define a susceptibility-like parameter which reaches a peaked maximum in the neighborhood, suggesting the presence of criticality. We finally speculate on the possible connections to Ramsey theory.

By Lucas Lacasa, Jacopo Tagliabue and Andrew Berdahl

Agent-Based Modeling of MEMS Fluidic Self-assembly

Abstract. The dynamics of fluidic self-assembly (FSA) of Micro Electro-Mechanical Systems (MEMS), recently demonstrated by experimental data, is modeled using interacting software agents. This method enables realistic simulations of FSA dynamics and represents a significant step ahead in the state-of-the-art of this field.

By Massimo Mastrangeli

  • Update (05 Oct '09): the abstract was accepted at IEEE MEMS2010! ( Thanks to SFI and all CSSS09ers!

The Individual and the Empire:The Effects of Agent-Based Emigration Behavior on the Emergence of Settlement Size Inequality in the Titicaca Basin, Bolivia and Peru

Abstract. Approximately 1000 years ago, from an evenly distributed population in the Andean highlands, a state-level society emerged with settlements ranging in size from hamlets to a large urban center of some 50,000 individuals. This working paper explores a mechanism that can produce inequalities in settlement-size distributions over time and space in the Titicaca Basin. Using agent-based modeling, we show that the cumulative effects of simple, individual-based migration optimization behavior can create a settlement rank-size distribution with the same formal qualities as that observed during the Tiwanaku Empire's apex. The model's general applicability is explored, improvements are suggested, and future directions proposed.

By Randy Haas, Jacopo Tagliabue, and Jeremy Barofsky

The Effect of Leverage on Financial Markets

Abstract When people get excited about their prospects on the stock market, they borrow money from the bank to invest. This leverage effectively couples the bank to the stock market. Thus, interest rates determine demand for stock, and demand for stock can determine interest rates. Does this interplay cause traders to naturally find a stable balance of leverage and aggressiveness? How do the behavioral traits of traders influence the stability of these interactions? Are there regulatory behaviors, such as limiting leverage or slowing margin calls, that would contribute to the overall health of the market? We present an economy consisting of a banking sector and an equity market, with traders transferring money between the two. Using an agent-based model, we will be able to examine how leverage couples the bank to the equities market. Furthermore, we can explore how different leverage strategies effects the stability of these markets.

By Nathan Hodas, Jacopo Tagliabue, Martin Schmidt, and Jeremy Barofsky

Creativity, Learning and Risk Orientation

Abstract Haven't we all come up with great ideas and later found that others have already done that? Don't we feel excited and potentially more creative when we learn newer concepts relevant to our interests? We all see highly creative people having diverse interests and want to emulate their creative success, however, it is difficult to open up to newer experiences just like that . . . and why should we unless there is a strong link between willingness to talk to strangers and being able to come up with a grand theory in physics? The enclosed working paper attempts to show that a single congitive mechanism is responsible for individual's learning and creative capacities: Creativity is just an internally driven learning mechanism. The paper shows that creativity is directly related to individual's openness to new expeirences and therefore learning, creativity and openess to new situations all connect together to define an individuals capacity for original thinking. A basic model in Netlogo tries to emulate the framework proposed in the paper.

By Murad Mithani

Revolutionary Fervor as Contagion: A Network Model of Rebellion

Abstract In this project, we model revolutionary activism on networks. Revolutionary fervor spreads through the network like a contagion, but depends on the revolutionary thresholds and grievance levels of each node. We provide for nodal removal and rewiring to better capture the underlying dynamics that drive revolutions and endogenize regime legitimacy. Our model deviates from existing work insofar as we arrange actors along a continuum, allowing for counter-revolutionaries and police to eventually be coopted into the revolution. This is a crucial condition for successful revolutions, which is too often gainsaid. Ultimately, we find that initial network structure has a negligible effect on long-run dynamics and that under many parameter settings the system equilibrates to a steady state after a transitory period and phase transition.

By Elliot Martin, Andrew Berdahl, Trevor Johnston, Eric Kasper, and Mahyar Malekpour

Modeling the Impact of Gender Imbalance on Marriage Markets

Abstract. This project examines the effects of gender imbalances in marriage markets. Examples of populations with gender imbalance are given, the effects of these demographics are explored, and recommendations for further research are given.

By Dave Brooks, Wendy Ham, Nathan Hodas, Brian Hollar, Liliana Salvador, and Guimei Zhu

Guns, Germs, and Steel: Guns, Germs, and Steel not included

Abstract Jared Diamond's (1997) argument that geographic topology played a central role in the timing and development of variable settlement and civilization sizes presents a testable hypothesis using agent based simulation. We examine early hunter-gatherer population dynamics on a global scale. Using recognized models for agricultural adoption, we can observe the transition from hunter-gatherer to agriculture dominated society. As of now, it certainly seems that geography played a major role in the spread of ideas and technology in pre-history. Maybe the best way to go from here is to have lunch with Jared Diamond.

By Nathan Hodas,Randy Haas, and Alexander Mikheyev

An Evolutionary Agent-Based Model of Problems and Solutions

Abstract We describe an evolutionary agent-based model of problems and solutions, and we explore its potential applications in topics such as: the origins of disciplinary boundaries, the effects of collaboration in problem solving, organizational intelligence, and innovation strategies.

By Dave Brooks, Wendy Ham, Nathan Hodas, Brian Hollar, and Liliana Salvador

Application of Network Clustering Methods to Gene Expression Profiling Data

Abstract We present the application of two new unsupervised clustering methods to gene expression data. The methods, partition decoupling (PDM) and commute time distance (CTD), are based upon the spectral analysis of the correlation structure of the data. Because they have the ability to reveal non-linear and non-convex geometries present in the data, spectral clustering based approaches are an improvement over typical linear clustering algorithms. Here, we apply these methods to a publicly-available gene expression data set, and demonstrate that we are able to identify cell types and treatments with higher accuracy than is obtained through other approaches.

By Rosemary Braun, Eric Kasper, Elliot Martin, and Corinne Teeter