Introduction to Human Systems Dynamics Seeing and Influencing Patterns

The Human Systems Dynamics Institute Announces…. Introduction to Human Systems Dynamics Seeing and Influencing Patterns
For Leading Edge:
Consultants, Facilitators and Coaches
Managers and Leaders
Professionals in education, sales, organization development, human resources, customer service, project management and information technology – any field where success depends on effective relationships, organizations or communities
Begin theHuman Systems DynamicsJourney!
What is Human Systems Dynamics?
Human Systems Dynamics (HSD) is a breakthrough approach to leveraging patterns of chaos and complexity for more effective and agile organizations, leaders and communities. It helps you see patterns and possibilities where others see chaos. It opens options for action to help you be more adaptable and flexible when you cannot predict or control.
Course Goal: See and influence patterns in human and organizational interactions.
This two-day course introduces you to the fundamentals of Human Systems Dynamics from simple rules to attractors and beyond. You will apply tools and techniques you learn so that you can see and influence complex patterns in your own practice. When you complete the course, you will have a toolbox that you and your clients can adapt to your own complex challenges as they emerge.
In This Course, You Will:
Use simple rules to support shared action
Experience self-organizing patterns in group activities
Set conditions for effective self-organization using the CDE Model
Adapt to multiple levels of constraint and stability through the Landscape Diagram
Manage equilibrium patterns through the Difference Matrix
Date: April 1 and 2, 2006, 9:00 to 5:00
Location: St. Paul, MinnesotaThe Sisters of St. Joseph Carondelet Center (adjacent to the College of St. Catherine campus)1890 Randolph Ave., St. Paul Facilitators and Coaches
Tuition: $900.00 All materials, snacks and parking are included. Reimbursement for travel, lodging, dinner, or miscellaneous expenses is not included.
Your Trainer: Glenda H. Eoyang, Ph.D., is the founding Executive Director of the Human Systems Dynamics Institute. As a pioneer in applications of chaos and complexity to organizations, Glenda teaches, writes and researches extensively. Her special interests include productivity in complexity, leadership, public policy, and decision making.
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What comes next? HSDP Certification
The Introduction to HSD begins the journey, and you are invited to continue your learning through the Human Systems Dynamics Professional (HSDP) Certification program.
Consider certification as a Human Systems Dynamics Professional. Through 10 days of engaging, emergent and experiential learning, you can develop a deeper understanding of the theory and practices of human systems dynamics. You gain the fundamentals, application tools, leadership and consulting practices to integrate HSD into your life and work. The training and certification will help you expand your leadership practice and increase your effectiveness.
In 2006, the HSDP Certification training will be held June 14-16, July 12-15 and August 16-18. HSDP Certification training is $5,000. If you attend Intro to HSD, you will receive a $500.00 discount on your HSDP tuition.
Invest in your future today!
To register or learn more about this and other learning opportunities, contact: Julia Wolter, Director of Operations 952-470-6080 or 866-473-4678 jwolter@hsdinstitute.org, http://www.hsdinstitute.org/events_learning.asp

Your conference destination is fast approaching!
2nd International Nonlinear Science Conference - 2006
March 10-12
Crete, Greece
We have a sparkling program lined up with presentations in psychology, biomedical sciences, agriculture, management, and economics.
In March, Crete offers the most amazing environment for visitors: a wide range of cultural events as well as a myriad of activities and fascinating sceneries from a sparkling blue ocean, sandy beaches, mountains and beautiful foliage. Making Crete, the ideal forum to discuss new scientific developments, their applications as well as it will help promote international cooperation
Keynote Speakers offer an incredible variety of topics:
Professor Dr. Peter Allen*
Complexity: the Challenge of a co-evolving Epistemology and Ontology”
Professor Dr. Tassos Bountis*
The New Science of Complexity: Promises and Challenges for the 21st Century”
Professor Dr. Stephen J. Guastello*
Leadership Emergence in Coordination-Intensive, Creative Problem Solving, and Production Groups
Professor Dr. Wolfgang Tschacher*
Self-Organization of Cognition
-------------------REGISTER, REGISTER, REGISTER, REGISTER----------------------
Early registrations rates run only until February 1, 2006.
Hurry and take advantage of the early bird prices.
Registration fees until Feb 1 are: US$275 for professionals and other non-students, $180 for students.The rates AFTER February 1, 2006 will be: US $300 (235 Euros) regular rates and US $205 (160 Euros) student rate. So, if you have not yet registered, please do so by visiting the conference website at:
www.societyforchaostheory.org/insc/2006.

Remember, that if you have never been a member of the SCTPLS before, a complimentary membership through the end of year is included with your conference registration. If you are paying by check mail it to:
SCTPLS, P. O. Box 484,
Pewaukee, WI 53072 USA
by or before the due date.
HOTEL REGISTRATIONS
The last day to register for INSC hotels is February 1 as well. There are four (4) hotels to be considered and all four are briefly described on the site. Please visit the INSC site, click on the ‘Hotel Info’ link and download the ‘Hotel Reservation Form’. The form contains all the information needed to make this a smooth, painless, and easy process. Note that all hotel prices include 2 meals a day.
If you should have any questions regarding hotel accommodations or any special needs, please direct your inquires to: mitos@stepc.gr.
We look forward to seeing as many of you in Crete, Greece in March 10-12, 2006.
Sincerely,
Ivelisse Lazzarini, Conference Chair, USA
Dimitrios Stamovlasis, Program Co-Chair, GREECE
Sifis Micheloyannis, Conference Committee, GREECE
Gernot Ernst, Conference Committee, NORWAY
Maria Karanika, Conference Committee, UK

Complexity and uncertainty and a new role for models

Dear TIAS members and other colleagues,
This is an invitation to participate in

Workshop 8, Complexity and uncertainty and a new role for models

To be held in the 3rd Biennial meeting of the International Environmental Modelling and Software Society, July 9-12, Vermont, USA, www.iemss.org/iemss2006

This workshop is organized by The Integrated Assessment Society (TIAS) by Claudia Pahl-Wostl and Marcela Brugnach

If there is one characteristic of today's environmental problems is its complexity. We are now faced with the challenge of solving problems where time delays, feedback loops, non-linearities and system interconnectedness make prediction particularly difficult. In this realm small events can have big effects, causes are multiple and separated in time, and problems transcend interdisciplinary arenas. Additionally, we, with our beliefs and perceptions about nature, are part of the problem to be solved influencing the way in which we identify and conceptualize reality, and drive inference from it. These characteristics make environmental problems intrinsically uncertain, difficult to predict and to manage. When dealing with these types of problems, computer models play a central role. They are crucial to structure our understanding of complex systems. A model constitutes an abstraction of a system existing in reality built for a particular purpose. As such, it can be manipulated, evolved and analyzed in place of the real system. However, developing an abstract description of a complex system is not easy. The uncertainty and indeterminacy present in complex systems, drive modelers to make subjective decision about the behavior of the system and its most relevant features. This implies embedding a series of nested, and sometimes iterative and evolving assumptions in the model. This in turn, incorporates uncertainty into the model at various levels; affecting the model, the way in which it is developed and the value of its inference.

But what does it mean for modelers and the way we do modeling? First, complexity affects the way in which models are implemented. Traditionally, models are though to be developed as a sequential of three main activities: conceptualization, implementation and evaluation. However, modeling complex systems requires an iterative process of model formulation, more like a trial and error approach, where modules at different levels of detail are considered in conjunction with different assumptions and hypotheses about how the real system works. As a result, the simple sequence of steps of conceptualization-implementation-evaluation, in reality becomes a series of cycles of conceptualization, implementation, re-conceptualization, code modification, implementation, etc. This iteration typically occurs over the course of time as new knowledge and ideas are generated and subsequently used to modify existing models. Second, from a conceptual standpoint, the presence of complexity shifts the goals of modeling from the creation of an exact replication of a system in which uncertainties ought to be eliminated, to being a creative process in which the different sources of uncertainties can be embraced. It enlarges the role of models as an “external” representation of reality. Models, and in particular the whole process of model development and application, may be perceived as part of a learning process to make transparent different perspectives and frames. Current model applications expand beyond prediction, to include exploratory analyses, communication and learning. This in turn, changes the type of knowledge needed and how this knowledge is elicited. But most important of all, it changes the inferences making possibilities.

Even though these are not novel ideas, and despite the increasing awareness about these issues, practical applications commonly fail in addressing the complexity and uncertainty of current problems. Generally, complexity gets diluted in simplifications done during model conceptualization and uncertainties are avoided as much as possible as being something undesirable. Commonly, once a model is developed, the assumptions and subjective decisions embedded into model representation are forgotten and only single causes of uncertainties are, sometimes addressed. For many, the presence of uncertainty completely invalidates the use of models to drive inference about a real problem. But, by avoiding complexity when modeling, aren’t we throwing the baby out with the bath water?

Complexity has brought a different way of viewing and understanding systems, in parallel, the modeling arena has seen the emergence of several new methods that are able to embrace these new concepts. However, despite these great advances, the goal of looking at a single best, simple and objective explanation still permeates the modeling exercise. We suggest that a more comprehensive way of dealing and handling complexity and uncertainties in modeling is still needed. A draft position paper was uploaded on the IEMSS 2006 webpage. The draft paper presented is a first attempt to do so. In it, we identified four major modeling purposes that are important for understanding and managing complex human environmental systems: prediction, exploratory analysis, communication and learning. Each of these purposes highlights different system characteristics, role of uncertainty, the properties of the model and its validation. We argue that uncertainty cannot be understood in isolation, but only in the context of a particular modeling activity and its importance is relative to the purpose for which the model is designed (e.g., when a model is developed for predictive purposes uncertainty needs to be eliminated, while when a model is developed for exploration uncertainty can be considered a source of creative thoughts). In this workshop we expect to expand these concepts making them operational, where tools, solutions and possible modeling directions can be selected according to the characteristics of the problem, the knowledge available and the modeling purpose.

The outcomes of the workshop will integrated into the position paper for publication in either Environmental Modelling, Integrated Assessment or another journal with all participants as co-authors. We invite all readers to provide their critical comments on the paper and contribute their own experience! Please contact Marcela Brugnach. mbrugnac@usf.uos.de if you are interested in participating.

TIAS website: www.tias-web.info

Three Exciting Workshops at the Baltimore Conference

Science at the Cutting Edge -- SCTPLS Annual Conference to be held at Johns Hopkins University, Baltimore, MD, August 4-6, 2006

If you haven’t begun to make your travel plans yet, here are three more reasons (for more information go to – www.societyforchaostheory.org)

Three Exciting Workshops at the Baltimore Conference

Three exiting workshops will start us off in Baltimore this year. Dr. Liebovitz (Florida Atlantic University) will conduct an introductory workshop in chaos theory and fractals, Dr. Glenda Eoyang (Human Complex Systems Institute) will discuss the applications of nonlinear dynamical systems to peace and conflict, and Dr. Mary Ann Metzger will offer a methodological workshop on the use of time series analysis and interpretation of results. Below are abstracts for each workshop as well as a biographical sketch of the workshop moderators.


Introduction to Fractals and Chaos Dr. Larry S. Liebovitch Professor & Interim Director, Center for Complex Systems and Brain Sciences
Florida Atlantic University liebovitch@clifford.ccs.fau.edu http://walt.ccs.fau.edu/~liebovitch/larry.html

This workshop will present an introduction to fractals and chaos and their applications. Fractals are things that have pieces that are ever smaller copies of the bigger pieces. A tree is fractal. It has ever finer branches that are smaller copies of the larger branches. Fractals can be used to better understand the structure and function of proteins, cells, the heart, and the brain. Chaos means simple systems that do surprisingly complex things. Chaos can be used to better understand the surprising things that molecules, cells, and people do. The topics covered will include: 1) Fractals: Introduction, Self-Similarity, Scaling, Dimension, Statistical Properties, 2) Chaos: Introduction, Phase Space, Sensitivity to Initial Conditions, Bifurcations, Analyzing Data, and Control of Chaos. The workshop will be based on the book, Fractals and Chaos Simplified for the Life Sciences, by L. S. Liebovitch, Oxford University Press, 1998 and a CD-ROM with curricula materials for a mathematics course for non-science students (http://www.ccs.fau.edu/~liebovitch/overview.html). The workshop does not require a background in mathematics.
Larry Liebovitch is a Professor and the Interim Director of the Center for Complex Systems and Brain Sciences at Florida Atlantic University (http://www.ccs.fau.edu/~liebovitch/larry.html). He has used nonlinear methods, including fractals, chaos, and neural networks to study genetic regulatory networks, the spread of biological and electronic infections, motions in proteins, the timing of heart attacks, and the swimming of one-celled organisms. He is the author or co-author of 2 books, 20 book chapters, 69 journal articles, and has given presentations in the U.S., Belgium, Brazil, Canada, China, Denmark, Finland, France Germany, Israel, Poland, and Sweden.

Complex Dynamics of Peace and Conflict
Glenda H. Eoyang, Ph.D.
Executive Director
Human Systems Dynamics Institute
geoyang@hsdinstitute.org

Peace is one dynamical pattern that can emerge from the complex interactions of individuals and institutions. Too often, however, human relationships generate conflict and strife. What can we learn from the insights of chaos and complexity about the conditions that shape patterns of peace or conflict on the individual, group, and international scales? How might that understanding shape individual or collective action?

This half-day seminar uses concepts and tools derived from nonlinear dynamics to explore systemic patterns of peace and conflict. Perspectives on peace and peacemaking will come from on-going research with national and international experts who analyze and take action to shape reconciliation and peaceful coexistence around the world. Participants will contribute core nonlinear tools and perspectives to help develop a coherent and useful model of nonlinear peacemaking.

By the end of the session, participants will:
· Identify essential similarities and differences in patterns of peace and conflict as they emerge in individual, small group, national, and international contexts.
· Recognize accepted “best practices” and acknowledged challenges for contemporary peacemaking.
· Describe the ways in which peace and conflict reflect patterns of nonlinear dynamics.
· Identify and apply tools and concepts from nonlinear sciences to understand the dynamics of peace and conflict.
· Recommend action toward peacemaking in a case study using tools and concepts of nonlinear dynamics.

Glenda Eoyang is founding Executive Director of the Human Systems Dynamics Institute (www.hsdinstitute.org), a research and consulting group developing theory and practice in human systems dynamics—the emerging field at the intersection of complexity and social sciences. She began her work with complex systems in 1989 and received the first doctorate in Human Systems Dynamics from Union Institute and University in 2002.

Eoyang's theoretical work covers a range of models and approaches. She has used nonlinear time series modeling, computer simulation modeling, and simulation games to explore the dynamics of human systems. As a trainer and consultant, she helps clients use insights from complexity to find options for adaptive action. As a long-time member of SCTPLS, she has shared her experiences and emerging learning at many past conferences. She has written numerous articles for academic and business publications on topics ranging from fractals for business administration to human computer interface design, youth gangs, productivity, large group events, team building, sustainability of organizational change, and program evaluation. Her books, like her presentations, are accessible and relevant to people who strive to understand and influence the dynamics of human systems of all kinds.


Drawing Conclusions from Time Series
Prof. Mary Ann Metzger
Department of Psychology
University of Maryland UMBC

This will be a practical workshop on methods for approximating behavioral processes underlying empirical time series using available software for linear (SAS Statespace) and nonlinear (Artificial Neural Network) approaches to approximation. Emphasis will be on methods applicable to difficult time series, including very short series, that are suspected to be nonlinear and non-stationary. The workshop will also cover the following topics:

Linear and nonlinear approximations for short-term prediction
Methods for describing behavioral patterns and summarizing dynamics
Non-stationary time series: Bayesian multi-process models
Using results for prediction, classification, and comparison
Examples: Application to observations on animal and human behavior
Nuts and bolts: Using available software to build models to approximate a process

Mary Ann Metzger has degrees in Mathematics and Psychology from the University of Connecticut, and postdoctoral work in Mathematical Psychology at the Rockefeller University, New York. She was a member of the Psychology Department faculty at UMBC from 1973 to 1999 and is now Professor Emerita. Her specialty is the application of systems dynamics to understanding psychological processes, including intellectual development, developmental disorders, and patterns of family relations. Relevant reading for the workshop: Mary Ann Metzger (1995) Tracking sequences of attractors in cognitive state-space. In R. Post and T. van Gelder (Eds.) Mind as Motion: Dynamics, Behavior, and Cognition, MIT Press.


David Pincus, Ph.D., SecretarySociety for Chaos Theory in Psychology and Life SciencesRegister online: www.societyforchaostheory.org/form.htmlcontact fellow members: sctpls@listproc.umbc.eduMail: SCTPLS, PO Box 484, Pewaukee, WI 53072, USAFax: 1+714-997-6780

Three Exciting Workshops at the Baltimore Conference

Science at the Cutting Edge -- SCTPLS Annual Conference to be held at Johns Hopkins University, Baltimore, MD, August 4-6, 2006

If you haven’t begun to make your travel plans yet, here are three more reasons (for more information go to – www.societyforchaostheory.org)

Three Exciting Workshops at the Baltimore Conference

Three exiting workshops will start us off in Baltimore this year. Dr. Liebovitz (Florida Atlantic University) will conduct an introductory workshop in chaos theory and fractals, Dr. Glenda Eoyang (Human Complex Systems Institute) will discuss the applications of nonlinear dynamical systems to peace and conflict, and Dr. Mary Ann Metzger will offer a methodological workshop on the use of time series analysis and interpretation of results. Below are abstracts for each workshop as well as a biographical sketch of the workshop moderators.


Introduction to Fractals and Chaos Dr. Larry S. Liebovitch Professor & Interim Director, Center for Complex Systems and Brain Sciences
Florida Atlantic University liebovitch@clifford.ccs.fau.edu http://walt.ccs.fau.edu/~liebovitch/larry.html

This workshop will present an introduction to fractals and chaos and their applications. Fractals are things that have pieces that are ever smaller copies of the bigger pieces. A tree is fractal. It has ever finer branches that are smaller copies of the larger branches. Fractals can be used to better understand the structure and function of proteins, cells, the heart, and the brain. Chaos means simple systems that do surprisingly complex things. Chaos can be used to better understand the surprising things that molecules, cells, and people do. The topics covered will include: 1) Fractals: Introduction, Self-Similarity, Scaling, Dimension, Statistical Properties, 2) Chaos: Introduction, Phase Space, Sensitivity to Initial Conditions, Bifurcations, Analyzing Data, and Control of Chaos. The workshop will be based on the book, Fractals and Chaos Simplified for the Life Sciences, by L. S. Liebovitch, Oxford University Press, 1998 and a CD-ROM with curricula materials for a mathematics course for non-science students (http://www.ccs.fau.edu/~liebovitch/overview.html). The workshop does not require a background in mathematics.
Larry Liebovitch is a Professor and the Interim Director of the Center for Complex Systems and Brain Sciences at Florida Atlantic University (http://www.ccs.fau.edu/~liebovitch/larry.html). He has used nonlinear methods, including fractals, chaos, and neural networks to study genetic regulatory networks, the spread of biological and electronic infections, motions in proteins, the timing of heart attacks, and the swimming of one-celled organisms. He is the author or co-author of 2 books, 20 book chapters, 69 journal articles, and has given presentations in the U.S., Belgium, Brazil, Canada, China, Denmark, Finland, France Germany, Israel, Poland, and Sweden.

Complex Dynamics of Peace and Conflict
Glenda H. Eoyang, Ph.D.
Executive Director
Human Systems Dynamics Institute
geoyang@hsdinstitute.org

Peace is one dynamical pattern that can emerge from the complex interactions of individuals and institutions. Too often, however, human relationships generate conflict and strife. What can we learn from the insights of chaos and complexity about the conditions that shape patterns of peace or conflict on the individual, group, and international scales? How might that understanding shape individual or collective action?

This half-day seminar uses concepts and tools derived from nonlinear dynamics to explore systemic patterns of peace and conflict. Perspectives on peace and peacemaking will come from on-going research with national and international experts who analyze and take action to shape reconciliation and peaceful coexistence around the world. Participants will contribute core nonlinear tools and perspectives to help develop a coherent and useful model of nonlinear peacemaking.

By the end of the session, participants will:
· Identify essential similarities and differences in patterns of peace and conflict as they emerge in individual, small group, national, and international contexts.
· Recognize accepted “best practices” and acknowledged challenges for contemporary peacemaking.
· Describe the ways in which peace and conflict reflect patterns of nonlinear dynamics.
· Identify and apply tools and concepts from nonlinear sciences to understand the dynamics of peace and conflict.
· Recommend action toward peacemaking in a case study using tools and concepts of nonlinear dynamics.

Glenda Eoyang is founding Executive Director of the Human Systems Dynamics Institute (www.hsdinstitute.org), a research and consulting group developing theory and practice in human systems dynamics—the emerging field at the intersection of complexity and social sciences. She began her work with complex systems in 1989 and received the first doctorate in Human Systems Dynamics from Union Institute and University in 2002.

Eoyang's theoretical work covers a range of models and approaches. She has used nonlinear time series modeling, computer simulation modeling, and simulation games to explore the dynamics of human systems. As a trainer and consultant, she helps clients use insights from complexity to find options for adaptive action. As a long-time member of SCTPLS, she has shared her experiences and emerging learning at many past conferences. She has written numerous articles for academic and business publications on topics ranging from fractals for business administration to human computer interface design, youth gangs, productivity, large group events, team building, sustainability of organizational change, and program evaluation. Her books, like her presentations, are accessible and relevant to people who strive to understand and influence the dynamics of human systems of all kinds.


Drawing Conclusions from Time Series
Prof. Mary Ann Metzger
Department of Psychology
University of Maryland UMBC

This will be a practical workshop on methods for approximating behavioral processes underlying empirical time series using available software for linear (SAS Statespace) and nonlinear (Artificial Neural Network) approaches to approximation. Emphasis will be on methods applicable to difficult time series, including very short series, that are suspected to be nonlinear and non-stationary. The workshop will also cover the following topics:

Linear and nonlinear approximations for short-term prediction
Methods for describing behavioral patterns and summarizing dynamics
Non-stationary time series: Bayesian multi-process models
Using results for prediction, classification, and comparison
Examples: Application to observations on animal and human behavior
Nuts and bolts: Using available software to build models to approximate a process

Mary Ann Metzger has degrees in Mathematics and Psychology from the University of Connecticut, and postdoctoral work in Mathematical Psychology at the Rockefeller University, New York. She was a member of the Psychology Department faculty at UMBC from 1973 to 1999 and is now Professor Emerita. Her specialty is the application of systems dynamics to understanding psychological processes, including intellectual development, developmental disorders, and patterns of family relations. Relevant reading for the workshop: Mary Ann Metzger (1995) Tracking sequences of attractors in cognitive state-space. In R. Post and T. van Gelder (Eds.) Mind as Motion: Dynamics, Behavior, and Cognition, MIT Press.


David Pincus, Ph.D., SecretarySociety for Chaos Theory in Psychology and Life SciencesRegister online: www.societyforchaostheory.org/form.htmlcontact fellow members: sctpls@listproc.umbc.eduMail: SCTPLS, PO Box 484, Pewaukee, WI 53072, USAFax: 1+714-997-6780

International Nonlinear Science Conference in Crete

"The list of speakers and topics for the International Nonlinear Science Conference in Crete (March 10-12) is now ready for viewing www.societyforchaostheory.org/insc/2006

We have a sparkling program lined up with presentations in psychology, biomedical sciences, agriculture, management, and economics.Early registration discounts will be available until February 1.

All other information you'll need about the conference, registration, and lodging is on the same web link.

We look forward to seeing as many of you there as possible.

Sincerely,
Ivelisse Lazzarini, Conference Chair, USA
Dimitrios Stamovlasis, Program Co-Chair, GREECE
Sifis Micheloyannis, Conference Committee, GREECE
Gernot Ernst, Conference Committee, NORWAY
Maria Karanika, Conference Committee, UK

Ninth International Conference on the SIMULATION OF ADAPTIVE BEHAVIOR

FROM ANIMALS TO ANIMATS 9

The Ninth International Conference on the SIMULATION OF ADAPTIVE BEHAVIOR

(SAB'06)

25 - 30 September 2006, CNR, Roma, Italy

The 9th SAB conference and workshops will take place in Rome, Italy, at the Conference Centre of the Italian National Research Council (CNR).

http://www.sab06.org/

Important dates:
Call for workshop deadline 20th January 2006
Paper submission deadline 20th March 2006
Camera ready submission deadline 10th May 2006
Conference start 25th September 2006
Conference end 30th September 2006
Tutorials 1st October 2006