From: Phillip Huggan (cdnprodigy@yahoo.com)
Date: Fri Sep 09 2005 - 13:38:02 MDT
>From fuzzy teen memories of time spent trying to unlock economics and finance systems secrets.
Chaos is the evolution of dynamic systems whose future cannot be predicted accurately due to extreme sensitivity to initial conditions. Systems exhibiting Chaos are deterministic, but usually not to a tractible extent. They would be simple system configurations to predict but for increasing interactions in time. Predicting object positions affected by multiple gravity fields such as planetary orbitals, whether there will be a tropical depression formation, paths of herding animals, the behaviour of a stock ticker in reaction to news, the final message produced by a kids game of telephone, the resting slot of the disk from the Price Is Right "Plinko" game; all affected by Chaotic interactions.
Complex Systems is the study of the bounded degree of order and function within a system. The behaviour of the system is not apparent from a study of the interactions between a system's components. A simple system can undergo a "phase shift" (usually by an addition of a component to the system) and become Complex, a process known as emergence. Giving rise to Complex Systems requires evolution, or neural nets, or genetic algorithms, or conscious creators. Examples of emergence include: when our ancestors became aware of self, adding just enough personnel to staff an oil-rig, the endocrine system of a 16 yr old blonde female undergoing puberty, the introduction of a new predator species to stablize an ecosystem, the successful profit maximizing strategies of actors in a dying commodity industry.
Elements from Chaos might be useful for building an AGI by revealing tractibility shortcuts. Maybe Complexity should be kept far away from a RPOP's goal structures, since this is the part we want to be predictable. An AGI utilizing emotions as its friendliness safeguard, would want to incorporate Complex Systems though. Latter seems harder to construct.
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