Complex Adaptive Systems: Energy, Information, and Intelligence: Papers from the AAAI Symposium
Mirsad Hadzikadic and Ted Carmichael, Cochairs
Complex adaptive systems (CAS) and related technologies have proven to be a powerful framework for understanding system-level phenomena across the physical, natural, and social sciences. We characterize a general CAS model as having a significant number of autonomous agents that use one or more levels of feedback; exhibit emergent properties and self-organization; or produce nonlinear dynamic behavior.
This symposium's theme addressed fundamental issues for understanding complex phenomena: Energy, Information, and Intelligence. This theme builds upon the previous years' focus of threshold effects (2009) and resilience, robustness, and evolvability (2010).
Energy in a CAS is often more than merely physical energy; it is anything that drives and constrains the system. Agents must cooperate and/or compete for limited resources, whether these resources are energy, power, food, money, or some other system resource. The success or failure of various agent strategies depends on their effectiveness in acquiring and utilizing these resources.
Information represents any form of verbal, nonverbal or even nonhuman communication. Information represents what the agents know or learn about their local environment. Papers relating to the theme of information may, for example, cover signal patterns and effects, signal processing, or information storage (memory). Flows of information itself may also be the focus of CAS research, such as in models of political dissent, social contagion, or the dynamical flows across networks.
Intelligence encompasses how agents react to any information that they acquire from the environment, as well as the system-level properties that emerge from these actions and reactions through patterns of correlated feedbacks. Thus, intelligence may refer to the agents themselves or to the system as a whole. Such intelligence can exist at almost any level of complexity, from simple examples of swarm intelligence to complex human cognition.