Sunday, April 10, 2016

The Paradox of Compromise and complex evolutionary Maps in Decision Making



This case study is primarily focused on process development of compromise mapping beyond Decision Making Mechanism.  Experimental methods in Cognitive Science have also been used during observational studies in order to capture sequential Map Matching Algorithms in Brain Process and circumstances surrounding compromises.  The numbers of Analogical Attributes with within “Compromise Map Profile” can imply to potential compromise paths between two types of Human Characters.  Comprehensive Knowledge of underlying Analogical Attributes within “Compromise Map Profile” can raise awareness about influences of complex genetic codes and instance parameters of Social Context on Human Behaviors. Knowledge inspiration can increase public understanding about Complex Decision Making, Emotional purge tragedy, and Behavioral Disorders. Untimely, this study determines and illustrates the source of good and bad Compromises, which is based on properties and characteristic attributes, within “Compromise Map Profile”.
Synthetic profiles have been used in terms of comparing Sequential Map Matching Algorithms in three structural stages model. Observational experience on Compromise Mapping illustrates how aggregated attributes develop from The First Map to “Final Compromise Map Profile”.
Conceptual Metaphorical Mapping provides imagining aggregated attributes through three phases of process interactions between two Human Characters. Besides, it makes transparency on process development of compromise mapping.
For example, two people encountered with chaotic situation in Social Context and they need to make decision by compromising strategy in order to prevent chaos.  A wide variety of compromisers’ profiles reduced in this paper due to time constraints. Two case studies have been carefully chosen among many other case study scenarios. These two case studies are involved with multiple instances of Brain Mechanisms, Decision Making Patterns, and paradox of Compromises.
According to the following two case studies highlight, good and bad Compromises can identify and compare through encapsulated attributes within “Final Compromise Map Profile”.
1- The first case study:
Men and Women were selected with similar genetic factors, similar environmental Influences, and common Superego Adjuster. Consider the following scenario analysis and possible events:  
Problem:
A stressful or dangerous situation can occur in Social Context; consequently, Survival Instincts would be activated in Brain of designated default profiles (Man and Woman). Two people encountered with chaotic situation in Social Context and they need to make decision by compromising in order to prevent chaos. Genetic Instinct and Gender Instinct modify Survival Instincts through Secondary Instinct.
1.1 Definition:
The output of “Instinct Component” produces and perpetuates Evolutionary Algorithms within The First Map, which contains Genetic, Gender, and General Instinct Codes. (Figure 1)
1.2 Analysis:
Similar Genetic Instinct Codes and similar environmental factors generate analogical attributes within“(1) Compromise Map Profile”. However, different types of Gender Instincts in Brain of two compromisers would probably show low analogical model among Gender Instincts. (Figure 1)
                                                                          



1.3 Learning outcome 1:
“(1) Compromise Map Profile” would probably encapsulate Analogical Attributes for Genetic Codes and Analogical Attributes for General Instinct Codes. But Non-analogical Attributes for Gender Codes would not be encapsulated. (Figure 2)
1.2.1 Definition for The First Map:
The Evolutionary Algorithms within The First Map interact with instance parameters of Superego and Ego environment.
1.2.2 Analysis:
Two compromisers interact with common Superego Adjuster (Instance of Social Context). Therefore, there is tremendous potential for having common principles and values with similar algorithms within Superego/Ego environment. Similar algorithms in Superego/Ego environment produce and perpetuate Superego/Ego Code within The Second Map (Iceberg Map). Besides, similar Genetic Codes and General Instinct Codes transfer from The First Map to The Second Map. (Figure 2)
1.2.3 Learning outcome 2:
“(2) Compromise Map Profile” would probably encapsulate analogical attributes among Superego/Ego Codes, analogical attribute for similar Genetic Codes, and analogical attribute for similar General Instinct Codes. Gender Instincts may be absent or subtle. (Figure 2)
1.3.1 Definition for The Second Map:
Evolutionary Algorithms within The Second Map (Iceberg Map) interact with Evolutionary Algorithms within the Logical Part of Brain. Interaction is caused by chemical modification, which generates and perpetuates new Evolutionary Algorithms, within The Third Map. (Figure 2)
1.3.2 Analysis:
Superego/Ego Code is modified by algorithmic mechanism in Logical Part of Brain and the new algorithmic mechanism controls The Third Map (Decision Making Pattern). (Figure 2)
1.3.3Learning outcome 3:
 “Final Compromise Map Profile” would probably encapsulate sufficient condition for analogical attributes for Decision Making Model. It contains analogical attributes for Superego/Ego, analogical attributes for similar Genetic Codes, analogical attributes for similar General Instinct Codes. Gender Instincts may be absent or subtle. Therefore, two compromisers have almost similar principles and values for Decision Making Model. Logical inferences are based on “a Good Compromise Model”.
2- The second case study:
Men and Men were selected with Genetic Diversity, Environmental Influences (Competitive environment), and individual Superego Adjuster (Lack of Superego Adjuster). Consider the following scenario analysis and possible events: 
Problem:
A stressful or dangerous situation can occur in Competitive Social Contexts; consequently, Survival Instinct and Competitive Instinct would be activated in Brain of designated default profiles (Man and Man). Social Context encapsulates complex domain and Competitive characters.
2.1 Definition for The First Map:
The output of “Instinct Component” produces and perpetuates Evolutionary Algorithms within The First Map, which contains Gender Instinct Code and General Instinct Codes. 
                                                                             



2.2 Analysis:
Similar Gender Instincts Codes and similar environmental factors with complex competitive modes would process analogical Gender Instinct and analogical General Instinct within “(1) Compromise Map Profile”. However, Diverse Genetic Instinct would not generate and encapsulate analogical attributes within “(1) Compromise Map Profile”. (Figure 3)
2.3 Learning outcome:
“(1) Compromise Map Profile” would probably encapsulate Gender Attribute and General Instinct Attributes (Competitive Attribute, Survival Attribute). But Genetic Instincts is eliminated in this Brain Process Mapping. (Figure 3)
2.2.1 Definition for The Second Map:
The Evolutionary Algorithms within The First Map interact with instance parameters of Superego and Ego environment. Interaction can create process for The Second Map in Brain.
2.2.2 Analysis:
Two compromisers interact with individual Superego Adjuster (Instance of Social Context). Therefore, there is little/no chance of having common principles and similar algorithms within Superego/Ego environment. Lack of Superego Adjuster within Social Context can fortify and enhance Ego functioning; in contrast, Superego would have weak cognitive functioning. Harmonic Balance and regular mediation between Superego and Ego can be deteriorated by Ego functioning and environmental factors.
Diverse paths of algorithms in Superego/Ego environment produce and perpetuate discrepant codes within The Second Map (Iceberg Map).  (Figure 3)
2.2.3 Learning outcome:
 “(2) Compromise Map Profile” would probably not encapsulate analogical attributes from the Superego/Ego Framework due to diverse paths of algorithms in Superego/Ego environment. (Competitive Mode in Superego/Ego can generally activate instance parameters of Hypocrisy). A good deal of Hypocrisy processes Inconsistent and Non-analogical algorithms within “(2) Compromise Map Profile”. Therefore, “(2) Compromise Map Profile” can be only encapsulated and instantiated Analogical Gender Attributes, Analogical Survival Attribute, and Analogical Competitive Attribute. (Figure 3)
2.3.1 Definition for The Third Map:
Evolutionary Algorithms within The Second Map (Iceberg Map) interact with the Logical Part of Brain. Interaction is caused by chemical modification, which generates and perpetuates new Evolutionary Algorithms (Strategic Map), within The Third Map. (Figure 3)
2.3.2 Analysis:
Dissimilar Superego/Ego Framework can modify algorithmic mechanism within the Logical Part of Brain, which controls The Third Map (Decision Making Pattern). The logical Part of Brain process wide variety of Strategic codes within The Third Map. Strategic variety beyond diverse algorithmic mechanism in Logical Part of Brain generates Non-analogical Attributes within “Final Compromise Map Profile”. (Figure 3)
2.3.3 Learning outcome 2:
“Final Compromise Map Profile” would probably not encapsulate Non-analogical Attribute of Superego/Ego Framework. Inconsistent Strategic Codes remain in The Third Map. However, analogical Gender Codes, analogical Survival Codes, and analogical parameters beyond Competitive Codes can encapsulate within “Final Compromise Map Profile”.
Therefore, two compromisers have different principles and values but they pretend to compromise due to own interest or advantage (Political Strategies). Decision Making Pattern and logical inferences is based on “a Bad Compromise Model”.
                                                                              



3. Conclusion:
The good and bad Compromises can identify and compare through encapsulated attributes within “Final Compromise Map Profile”. The Good Compromise Mapping Profile requires that “Final Compromise Map Profile” encapsulates multiple analogical attributes, which instantiate through Instincts, Superego/Ego, and Logical Part of Brain. The Good “Compromise Mapping Profile” provides good potential compromise paths between two types of Human Characters. (Figure 4)
The first case study shows that “Final Compromise Map Profile” encapsulated sufficient attributes and met the minimum requirements for Good Compromise Mapping.
The second case study shows that “Final Compromise Map Profile” encapsulated insufficient attributes and the minimum (mandatory) requirements were not fulfilled.  Similar Survival, Gender, and Competitive Instincts would not ensure Good Compromise Mapping Profile. Similar Survival Instincts promote and suggest temporary regulations in order to achieve Compromise Mapping Profile. Politicians used to engage with this type of Compromise Mapping Profile; therefore, they are not confident with their own unreliable Compromises. Common Competitive Instincts between two compromisers generate Super-sized Hypocrisy in the Brain. Hypocrisy Mode can lead to obstruct Superego strength and modify Harmonic Balance between Superego and Ego. Therefore, “Final Compromise Map Profile” would no longer remain in power. (Figure 4)
                                                                                



Observation:
“(1) Compromise Map Profile” and “(2) Compromise Map Profile” are used in this study as imagining Maps in terms of improving transparency for development of aggregated attributes within “Final Compromise Map Profile”
Observation:
Superego Adjuster can modify Algorithmic Structure within Superego/Ego in the long term. Superego/Ego can modify Algorithmic Structure within Logical Part of Brain in the long term.
Observation:
Algorithmic parameters in Social Context develop according to Global Variables.
Observation:
Algorithmic parameters in structure of Global Variables articulate and create according to economic perceptions and political preferences within Competitive World.
Observation:
Political preferences in Competitive World are articulated and created by Big Corporations and Elites.
Observation:
System developers modify algorithmic parameters in Social Context. Those algorithmic Parameters fortify Ego strength, mistrust among people, and empowering Hypocrisy.
Observation:
Complex parameters in Social Context solve with Complex solutions because of low cost performances and measurable short term outcome. Systems Owners are not concern about possible side-effects of Complex Solutions. Systems Owners believe that they approach and define optimal solutions due to Optimal Economic Growth in short term. These types of solutions create multiple sides-effects in long term.
Observation:
Certain old cultures (within Superego Adjuster) modified Gender Instincts for men and modification ensured reliability for Compromising, Regardless to number of encapsulated Attributes in “Compromise Map Profile”.
Observation:
Systems Owners approach sometimes Hypocrisy Mode in order to reduce costs, build a competitive advantage, and maximize Harmonic Balance in Social Context in short term. However, they would not target possible side-effects of Hypocrisy over implementation due to low level implementation knowledge.