Friday, August 26, 2011

A Common Strategy Perspective in Democratic Systems

The primary objective of an algorithmic strategy, beyond managing global variables, is to ensure maximum system performance reliability. Achieving this level of accuracy and security requires optimal resource allocation across various system layers. When economic allocation models function efficiently, these resources will be available optimally within system platforms.
System Owners focus on economic performance and work to eliminate entities that might conflict with this goal. Any overhead cost on the system platform is considered detrimental to the economy. According to observational studies, investment in maintaining harmonic balance in Biological Systems is often viewed as an additional overhead for Non-Biological Systems. As a result, System Owners tend to endorse austerity measures to perform tasks more cost-effectively in Non-Biological Systems. However, these austerity measures, segregation of operative layers, and low social accountability on the system platform may diminish harmonic balance within Biological Systems.
In undemocratic systems, Systems Owners prioritize economic considerations in their global strategies. Much revenue is often reserved for the owners' retirement security, while profits are directed toward hierarchy layers or used to satisfy malicious desires. This approach may ultimately eliminate the potential for harmonic balance within the system, as such balance is viewed as a social burden in purely economic systems.
In contrast, Systems Owners in democratic systems recognize that a significant portion of the income derived from system performance should be saved and distributed equitably across all system resources. This approach supports broader resource sustainability and fosters a healthier system environment.

Chaotic Environments Dominate the Subconscious Component

An observational study suggests a strong analogy between humans and robots when individuals in chaotic environments are impacted on their li...