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Volume 42, No. 3 • May-June 2006
In the Spotlight

Engineering Optimal Individuals

Pages 1 | 2 | 3 | 4 | 5

Overall Summary Relationships Structure

The context for the work in this paper is illustrated by the relational logic diagram in Figure 6.



Figure 6 — Overall View of Context for Individual Design Results.

The focus on engineering design of optimum individuals is emphasized at the center of the diagram. The reference to management strategies, interpersonal communication, converting fear to passion and synergistic collectives is depicted as part of the boxes at the upper right, just above lower left, just below middle right and at the extreme lower left, respectively. Management strategies are part of the constraints that enter at the top of the design box. Other constraints are physical laws. The interpersonal communication is targeted toward enriched information and synergistic collective results, as well as state of health and connections to reality (seeking definitive markers in an attempt to identify "truth"). This is driven by the Collective Synergy box and the Unique-Signal communication strategy box. The metric is furnished by communication entropy. The inputs to the individual engineering design box include exergy for consumption, in addition to the information. The Interpersonal Communication box is also served by the output of the Individual Design box. Latent effects (effects that have been instigated earlier, but contribute to later actions) contribute to several boxes. These are often limiting behaviors and biasing filters. The main individual outputs discussed earlier are shown at the middle right. Some of these are used in the Evaluation, Feedback box. The main threats shown are from the Human Limitations box and from the Fear and Games box, the latter of which has inputs from the box that depicts converting fear to passion and the Game Theory box. The Evaluation, Feedback box monitors the outputs and is used to contribute to the individual traits. All of this helps portray the overall context and helps illustrate why both top-down and bottom-up views contribute to overall understanding.

Mathematical Assessment of the Engineering Design of Individuals

All of the structure shown in Figure 6 can be mathematically analyzed. Portions have been done previously [Refs. 1, 2 and 3]. While the overall analysis is beyond the scope of this paper, the analysis of the engineering design of individuals shown in Figure 4 will be developed here. The progression that led to the model portrayed in Figure 4 was logically derived. The actual success of applying the model can be enhanced by using mathematically based metrics. The aggregation of the factors in Figure 4 is most effectively done through a strategy such as Markov Latent Effects aggregation [Ref. 8]. In Markov Latent Effects aggregation, early effects are derived and used to influence later effects in a structure that reflects the sequence of influences. An example latent effects structure is shown in Figure 7.

Each module in Figure 7 represents a weighted sum, so that the input values are each multiplied by an associated weight and added. Input values have positive response to value, so that, for example, a value of zero has minimum attribute, and a value of one has the maximum positive attribute. A value of 0.5 is considered "average." The outputs represent a resultant value score. Example input weights are shown, where the sum of the weights into each module is one. The weights vary depending on the application. Those shown for the example are postulated for the "Self-Actualization" output.

As an illustration, a calculation for Self-Actualization was made using the following inputs, given as interval values in order to represent input uncertainty:

Environment: 0.6, 0.7
Interpersonal Communication, Information: 0.8, 0.9
Human Limitations: 0.3, 0.5
Human Threats: 0.7, 0.8
Natural Threats: 0.8, 0.9
Management Controls: 0.8, 0.9
Society Constraints: 0.4, 0.6
Physical Laws: 0.8, 0.9
Self-Actualization Feedback: 0.7, 0.9
Collectives Feedback: 0.3, 0.4

The resultant Self-Actualization score is 0.60, 0.74, which is a little above average.


Figure 7 — Markov Latent Effects Model for Individuals.

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