University of California Multi-Campus Complexity Events 2010-2012

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Previous years

2010 calendar webcast test Co-Directors: Douglas R. White and Laurent Tambayong - CLICK HERE for past 2009-2010 events.
Our dates are chosen so as not to conflict with the UCLA Marschak colloquium 2010-11 Calendar printable (two saturday 3.5 hour conferences with lunch provided to be scheduled)

COURSE CREDITS- Grad and Undergrad

  1. Course:_social_networks_and_complexity UCI fall:SOC SCI 240A (fall 72100 winter 71500) grad and undergrad 1.33 credits per quarter. Instructor Douglas R. White, Winter SOC SCI 240B, Spring SOC SCI 240C
  2. UCLA fall: Anthro M193/Hum CS M193P (both undergrad) and Anthro 294 (grad). Journal Club, Human Complex Systems Seminar. 1 unit. Instructor: Dwight Read, and Course Coordinator: John Bragin,
  3. UCSD fall:ANTH 203 "Four-Campus Video conference" seminar (undergrads may also take for credit) Instructor: Geoff Braswell anthro,



  1. UCI: AIRB 3030 UCI (Anteater I&R Bld) Soc Sci 240A fall - 240B winter -240C spring D.R. White, Bill Alvarez 824-4136
  2. UCLA f-w-s 285 Powell Library
  3. UCSD f-w-s UCSD 260 Galbraith Hall Anth 203 (G. Algaze) "Four Campus Video Conference" in Human Social Complexity

Nonconflicting dates for Marschak talk October 9? TBA, October 23? TBA, November 6? TBA, November 20? TBA, December 4? TBA

Fall Quarter 2010

Marschak Colloquium dates for 2010-2011 are:

  • October 1, 15, etc. in Fall 2010
  • January 14, 28, etc. in WInter 2011
  • April 8, 22, etc. in Spring 2011.

HSC Videoconference Friday Sept 24 2010 Douglas White

Causal analysis networks for early ethnographically well-studied populations - pdf of paper - Sept24UC4 2010 Camtasia Replay - Podcast video

Abstract: Results and strategies are illustrated for using a newly completed R package for cross-cultural or cross-community samples, Rccs, which generates potential causal inferences from coded data for ethnographic studies. It factors out network "peer effects" of spatial and shared cultural history, imputes missing data, and generates networks of potential causal relations among variables. These can be evaluated by Pearl's causal graph theorems for identifiable causal structures. Illustrations are given for a large network of variables from the Standard Cross-Cultural Sample and for a small time-series sample of South Asian villages undergoing transformation from a Jajmani patron-client to market exchange. It will also be applied to Lewis Binford's (2000) forager sample. Multi-level peer effects can be accommodated in these analyses. *Rccs* is used in UCI undergraduate science writing classes and is open access under the Gnu license for use in university classes worldwide.

recording with Relay: the tour - Get a UCI Camtasia Relay account

Spring 2010 talk

HSC Videoconference Friday Oct 8 2010 Yen-Sheng Chiang

1:30-3:15 Yen-Sheng Chiang, Asst. Professor, Sociology, UCI. pdf of the ppt - Podcast video

Cooperation Dynamics in Networks When Cued by the Structural Attributes of Nodes

Recent research endeavors in science investigate how cooperation evolves in complex networks. In the models, the network is either exogenously given or is formed endogenously. In either case, actors are modeled to occupy the nodes, play the prisoner’s dilemma game with their network neighbors and adapt behavior in reference to either their local network neighborhood or the whole population. Yet, in these models an actor’s decision of cooperation or defection in the game is independent of the network structure. A cooperator, for example, would cooperate unconditionally with all his network neighbors despite their differences in network positions. In this talk, I introduce a new direction for modeling cooperation dynamics in networks where an actor’s decision making can be cued by the structural attributes of nodes. In the new model, cooperators are conditional in the sense that they follow some rules that govern whether they would cooperate or defect dependent on the network structural properties, such as betweenness, clustering and degree, of the nodes they occupy as well as their neighbors’. Simulating the evolution of cooperation across a variety of networks shows that conditional cooperators who are selective in choosing the recipients of cooperation based on the cues of nodal attributes increases the pervasiveness of cooperation across the population.

  1. 3030 Anteater I&R Bld (AIRB) UCI
  2. 285 Powell Library UCLA
  3. 260 Galbraith Hall UCSD
  4. 250 Olson Hall UC DAVIS UC Davis classroom technology Services Bill Sykes Academic Technology (530) 752-2133

HSC Videoconference Friday Oct 22 2010 Dwight Read

Dwight Read, Professor of Anthropology, UCLA. - Podcast video

"Mathematical Modeling of the Logical Structure of Kinship Terminologies"

Streaming video in Flash - !Kung San Kin Terms

Abstract: Kinship systems in human societies as expressed through kinship terminologies are cultural constructs built over, but not determined by, the biological facts of reproduction. Historically, kinship terminologies have been presumed to be a natural taxonomy with kin terms labeling categories of genealogically defined relations, despite extensive ethnographic evidence to the contrary. Instead, kinship terminologies are a system of symbols forming a computational system (a kin term space), much like numbers are a computational system of symbols. Consequently, a terminology has a generative structure and that generative structure can be modeled algebraically. The algebraic modeling provides a logical account for the properties of kinship terminologies and a way to meaningfully explore structural differences among terminologies. The idea of a kinship space will be introduced as a way to integrate together the concepts of a family space, a genealogical space and a kin term space.

HSC Videoconference Friday Nov 5 2010 Cancelled and rescheduled

Winter Quarter 2011

2011 calendar

Unscheduled as yet George Barnett

George Barnett, Communications, UCDavis. Effects of communication networks on conflict and cooperation

(Winter-Spring Speaker suggestions from UC Davis)

  • Diane Felmlee and Bob Farris--Sociology. They are doing interesting work on network effects on youth violence.
  • Bob Huckfeldt--political science. He is doing experimental networks research on cooperation and voting.
  • George Barnett--communications. He is doing work on the effects of communication networks on conflict and cooperation.
  • UCSD

HSC Videoconference Friday Jan 21 2011 Douglas R. White rescheduled to Feb 18

UCI students - sorry for the postponement. You can review past speakers as a subject for your paper. For example, we had a talk by at Jeff Brantingham, UCLA Anthropology at "Simulating the foraging behavior of criminals" (in LA) Our talk is viewable only in Real media .rm But a revised version was later published in a 5-page paper at in Pubs of the Natl Academy of Science Other publications of this UCLA group are at

HSC Videoconference Friday Feb 4 2011 Dwight Read

Working Memory Score: Chimpanzees 2, Humans 7 bitly

A background paper for the talk

Abstract: We tend to assume qualitative differences in mental capacities must derive from qualitative differences along some cognitive dimension. With working memory, however, the quantitative difference between 2 ± 1 for Pan and 7 ± 2 for Homo sapiens underscores major qualitative differences in mental capacities between Pan and Homo. With working memory of 2 ± 1, chimpanzees cannot engage in recursive mental processes and so language as we know it is closed off to them. Theory of Mind seems to require more extensive working memory than is available to Pan, hence the repeated failure to demonstrate Theory of Mind capabilities in Pan. Culturally constructed systems of kinship, the foundation upon which human forms of human social organization are based, depend on recursive reasoning and so we do not find the evolutionary roots of culturally constructed systems of kinship in chimpanzee social systems. The difference of 5 in the size of working memory, then, has enormous implications for differences in the cognitive capacities of Pan versus Homo sapiens. In this talk I will discuss the evidence showing that working memory for Pan is 2 ± 1. Then I will review the clear relationship we find between the increase in working memory size when going from Pan to Homo sapiens and changes in the conceptual prerequisites for the form of lithic artifacts produced in association with our encephalization over the time period from 2.6 million years ago to the Upper Paleolithic.

HSC Videoconference Friday Feb 18 2011 Douglas R. White, Complex Causality research team

Evolutionary Causality: Discussions, Demonstrations, Possibilities link: - Podcast video
iTunesu UC_Irvine Social Science (Look under Social Sciences for our logo) or try

R2sls package features
Previous talks on causality: Jan 2010 - Sept 2010
Upcoming talks on causality and artificial intelligence: Greenland - Decter

Abastract. Bring your laptop to explore the intersci wiki pages on Evolutionary Causality for this free-ranging discussion on three campuses by research project and audience members. The project discussion explains how causal analyses for cross-cultural and cross-national studies is brought under the general rubric of Galton’s problem and Evolutionary causal graphs (title of the NSF proposal). We want to make accessible sharable databases, open access software, and experience on how to develop causal analysis research projects. There will be two speakers in spring term on causality and machine learning.

Demonstration projects and possibilities

SCCS Causal Graph model for Evil Eye and Moral Gods

&SCCS R package install

How we began and the Causality software with the 186 society SCCS

Doug White and Scott White at UCSD, Tolga Oztan at UCI:

The Eff and Dow software (2009) and classroom use of Two-Stage Least Squares with missing data imputation and controls for nonindependence (Galton's problem).

How to build new datasets: the 339 society forager database and possibilities for Cross-National Studies

Doug White; Giorgio Gosti and Tolga at UCI; and Zeev Maoz at UC Davis

Components of a database
Row normalized W matrices (e.g., distance, language, political proximity) used to model nonindependence among cases
The auxiliary database for imputing missing data
Variable databases
Foragers - Codebook in Excel
Standard Cross-Cultural Sample - SCCS - SCCS Codebooks
Cross-Polity databases

Evolutionary Causality

Doug & Giorgio, late arrival by Duran

Duran at UCI & Doug: Forager societies, Fractalities and Marriage Networks from KinSources: Research question: If the fractal basis of family size is usually four, but varies up to six in Australia and elsewhere, is it the broader extension of marriage networks that is the cause of this variation?
Ethno-Atlas of Coded Data for Kinsources Social Networks
Foragers and Fractalities

HSC Videoconference Friday Mar 4 2011 John Bragin

John Bragin, Lecturer and Graduate Coordinator, Human Complex Systems Program, UCLA Personal Website - streaming video at iTunesu UC_Irvine Social Science (Look under Social Sciences for our logo) or try

Foundations of Agent-Based Modeling: With Some Objections and Their Refutation

Abstract: Agent-based simulation modeling is the core methodology of complex systems science. In an agent-based simulation model of a complex adaptive system (in biology or society) each agent is explicitly represented. This includes the perceptual, cognitive and behavioral capacities of each type of agent and the capacities for agents to change in their interactions with other agents and the environment. Agents are autonomous: They act on their own behalf, without direction by a global design or central controller, although they are certainly influenced by other agents and the constraints and opportunities imposed and provided by the global patterns resulting from agent interactions. Although an agent-based simulation model can be written using mathematics, it is more usual today to use a high level programming language consisting of algorithms. Nevertheless, such programs (unlike even the most precise prose) are as rigorous as mathematical proofs, because they must “be complete, consistent and unambiguous if they are to be capable of being executed on a computer. On the other hand, unlike mathematical models, agent-based models can include agents that are heterogeneous in their features and abilities, can model situations that are far from equilibrium, and can deal directly with the consequences of interactions between agents.” (Gilbert, 2008)

Spring Quarter 2011

March 25 Cesar Chavez day ==Suggested invited speakers for spring, themes of Causality, Complex networks, and others Maurizio Seracini or Robert Moyzis or Judea Pearl==

  • date to be confirmed
  • Maurizio Seracini
  • Robert K. Moyzis - Professor of Biological Chemistry. Human Genomics Coordinator for the Institute for Genomics and Bioinformatics. Prior to joining the Faculty at UCI, Director of the Center for Human Genome Studies at Los Alamos National Laboratory, the first Genome Center to be established as part of the Human Genome Project (HGP). YouTube - blog

Are We Evolving?

HSC Videoconference Friday Apr 15 2011 Complex causality research team

Doug White, Tolga Oztan, Giorgio Gosti, Duran Bell URL:

  • A synthetic approach to historical causality POSTPONED TO FALL (the group will meet at UCI)

HSC Videoconference Friday Apr 29 2011 Rina Dechter

Abstract. I will describe three classes of algorithms which have become central in Artificial Intelligence and general computer science. These algorithms involve search over graphical models such as constraint networks, Bayesian networks, Markov fields and influence diagrams, which are the most commonly used representational scheme in tasks such as design, scheduling, diagnosis, planning and decision making with applications in medical diagnosis, man-machine interface, electronic commerce, robot planning, troubleshooting, economical prediction, market analysis, natural language understanding and bio-informatics applications. It is known that all these tasks are computationally hard, and while substantial progress has been made in the last 2-3 decades pushing the computational boundaries far ahead, numerous real-life problems are still out of reach for current technology. Advance in exact or approximate methods is crucial, with potential impact across many computational disciplines.

In this talk I will provide an overview and describe progress made in the past 5 years on developing algorithms that can adapt to the problem's structure.

More information can be found at:

Bio: Rina Dechter is a professor of Computer Science at the University of California, Irvine. She received her PhD in Computer Science at UCLA in 1985, a MS degree in Applied Mathematic from the Weizmann Institute and a B.S in Mathematics and Statistics from the Hebrew University, Jerusalem. Her research centers on computational aspects of automated reasoning and knowledge representation including search, constraint processing and probabilistic reasoning. Professor Dechter is an author of “Constraint Processing” published by Morgan Kaufmann, 2003, has authored over 100 research papers, and has served on the editorial boards of: Artificial Intelligence, the Constraint Journal, Journal of Artificial Intelligence Research and Logical Method in Computer Science (LMCS). She was awarded the Presidential Young investigator award in 1991, is a fellow of the American association of Artificial Intelligence, she was a Radcliffe fellow 2005-06 and the “Association of Constraint Programming award (ACP 2007) for research excellence.

HSC Videoconference Friday May 13 2011 Sander Greenland

Abstract: In controversial topics and nonexperimental settings, bias (not random error) is the core obstacle to causal inference. Causal diagrams (graphical causal models, especially directed acyclic graphs or DAGs) provide the easiest way to see bias sources, and provide insights into how to deal with those sources. Because of this property, these diagrams have become part of core epidemiologic methods teaching in several programs, including Harvard and UCLA. This talk will provide an overview to illustrate the power and limitations of causal diagrams in this role.

video 2010 "Predictive Diagrams: Backing off from Causality in DAGs"

HSC Videoconference Friday May 27 2011 Maksim Kitsak


Maksim Kitsak - Cooperative Association for Internet Data Analysis (CAIDA) in SDSC at UCSD -

Title: Do bipartite networks have metric structure? Flyer for talk See UCI iTunesu - Pdf of Powerpoint

Abstract: Many social, biological and technological systems can be conveniently represented as bipartite networks, consisting of two disjoint sets of elements along with edges connecting only elements from different sets. Many of such systems are characterized by high values of bipartite clustering coefficient. We also find that pairs of elements in these bipartite systems tend to have many common neighbors. We present a natural interpretation of these observations. We suggest that elements of the above bipartite systems exist in underlying metric spaces, such that the observed high clustering is a topological reflection of the triangle inequality, the key property of metric space. We propose a simple stochastic mechanism of formation of bipartite networks embedded in metric spaces. We prove that this mechanism is able to reproduce the observed topological properties of bipartite networks. We also discuss the possibility of constructive embedding of real bipartite systems into metric spaces.

Should we have a fall focus on games and networks, networks and conflict, network dynamics, business networks?

Prominent paper on games and networks: please add to the list of possible colloquia topics or speakers

Ballester, Coralio, Antoni Calvó-Armengol & Yves Zenou, 2005. "Who’s Who in Networks. Wanted: The Key Player" Econometrika 74(5):1403-1417.
Ranjay Gulati Chua Tiampo Professor of Business Administration, Harvard Business School - books and papers.

Alternation of Friday 2010-2011 time-slots with UCLA Marschak talks

Marschak Colloquia, UCLA

Academic year 2011-12 UCSD host site at SDSC (DANCES)

UCSD host site at SDCS
Impromptu organization focusing on research problems