Most interesting phenomena in natural and social systems include constant transitions and oscillations among their various phases.  Wars, companies, societies, markets, and humans rarely stay in a stable, predictable state for long.  Randomness, power laws, and human behavior ensure that the future is both unknown and challenging.  How do events unfold?  When do they take hold?  Why do some initial events cause an avalanche while others do not?  What characterizes these events?  What are the thresholds that differentiate a sea change from a non-event? 

Complex Adaptive Systems have proven to be a powerful tool for exploring these and other related phenomena.  We characterize a general CAS model as having a large number of self-similar agents that: 1) utilize one or more levels of feedback; 2) exhibit emergent properties and self-organization; and 3) produce non-linear dynamic behavior.  Advances in modeling and computing technology have led not only to a deeper understanding of complex systems in many areas, but they have also raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves differently. 

Threshold effects are found all around us.  In economics, this could be movement from a bull market to a bear market; in sociology, it could be the spread of political dissent, culminating in rebellion; in biology, the immune response to infection or disease as the body moves from sickness to health.  

Our goal is to bring together researchers from diverse fields who study these complex systems using the tools and techniques of CAS.  We will highlight threshold effects in various disciplines as one avenue towards exposing common dynamics that are found in these disparate domains.  In the past, knowledge gained in each domain about threshold effects has remained mostly exclusive to that domain, especially when the disciplines are far apart.  It is our belief that by bringing together scholars who study these phenomena, we can leverage a deep knowledge of one domain to gain insight into others.