Complex Adaptive Systems: Resilience, Robustness, and Evolvability: Papers from the AAAI Fall Symposium
Mirsad Hadzikadic and Ted Carmichael, Cochairs
Companies, societies, markets, and humans rarely stay in a stable, predictable state for long. Yet all these systems are characterized by the notable persistence of some key attributes which maintain their identities, even as their constituent parts change and adapt to new environments. What is it about these systems that define their identity? How do we characterize them? What are the forces that allow a system to persist, even in the face of a radically new environment?
Complex adaptive systems (CAS) and related technologies have proven to be powerful tools for exploring these and other related phenomena. We characterize a general CAS model as having a significant number of self-similar agents that utilize one or more levels of feedback; exhibit emergent properties and self-organization; produce nonlinear dynamic behavior.
Advances in modeling and computing technology, including CAS, have led to a deeper understanding of complex systems in many fields in the natural, physical, and social sciences. These developments have raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves in different ways.
For some practitioners in the field, the terms "resilience" and "robustness" may seems largely redundant. Indeed, there are many other terms from various domains that overlap as well: from "basins of attractions" (physics, mathematics), to "homeostasis" (biology), to "sustainability" (ecology). This is precisely the point: different disciplines often have their own language, even as they are describing identical or similar phenomena. We therefore invite participation from researchers across a wide range of disciplines, in the belief that a deep understanding in one domain may lead to greater insight into others.