Chapter 3. Habitual Domain and Decision Makings in Changeable Spaces
3.1. Definition and Elements of Habitual Domains
Example 1 illustrates that one’s judgment is greatly affected by his/her perception frames, the size and shape of the lighted areas of Figure 1. The perception frames are largely determined by the parameters of our human behavioral systems.
Being able to understand and utilize these parameters is therefore a vital step to making decisions efficiently and effectively in changeable spaces.
Habitual domains was first suggested in 1977 (Yu 1977) and further developed (Chan and Yu 1985; Yu 1980, 1981, 1985, 1990, 1991, 1995, 2002 and quotes therein) by Yu and his associates. It states that over a period of time, the set of ideas and concepts which we encode and store in our brain can gradually stabilize in certain domain, know as Habitual Domains (HDs); unless there is an occurrence of extraordinary events, our thinking processes will reach some steady state or may even become fixed. This phenomenon can be proved mathematically (Chan and Yu 1985;
Yu 1985).
Being aware of the habitual ways of our decision making is important for us to clarify fuzziness, make better decisions and avoid costly mistakes. To better understand the concept of HDs, let us briefly introduce the elements of HD, which are important parameters in the human behavioral systems.
Habitual domains at time t, HDt, include the following four sub-concepts:
(i) Potential domain, designated by PDt, is the collection of all ideas and operators which can be potentially activated with respect to specific events or problems by one person or by one organization at time t. In general, the larger the PDt, the more likely that a larger set of ideas and operators will be activated, holding all other things equal.
(ii) Actual domain, designated by ADt, is the collection of ideas and operators which are actually activated in our minds at time t. Note that not all the ideas and operators in the potential domain can be actually activated. Also note that the ADt is a subset of the PDt, that is ADt ⊂ PDt.
(iii) Activation probability, designated by APt, is defined for each subset of PDt
and is the probability that a subset of PDt is actually activated or is in ADt. For example, people who emphasize profit may be more likely to activate the idea of money, while people who study mathematics may be more likely to generate equations.
(iv) Reachable domain, designated by RDt, is the collection of ideas and operators which can be generated from a given set in an ADt. In general, the larger the idea set and/or operator set in ADt, the larger the RDt.
At any point in time, without specification, HDt is the collection of the above four subsets. That is,
HDt = {PDt, ADt, APt, RDt}
When there is no confusion, the subscript “t” may be dropped as to simplify the
presentation. Recall that it is humans that make decisions. Understanding human behavioral systems plays a vital role in making good decisions. The complex processes of human behaviors have a common denominator resulting from a common behavior mechanism. The mechanism depicts the dynamics of human behavior. Based on the literature of psychology, neural physiology, dynamic optimization theory, and system science, Yu (1980, 1981, 1985, 1990, 2002) described a dynamic human behavior mechanism as presented in Figure 2 which is briefly explained below:
(i) Box (1) is our brain and its extended nervous system. Its functions may be described by the four hypotheses (H1-H4) in Table 1.
(ii) Boxes (2)-(3) represent two basic functions of our mind, explained by H5 in Table 2.
(iii) Boxes (4)-(6) represent how we allocate our attention to various events, described by H6 in Table 2.
(iv) Boxes (8)-(9), (10) and (14) represent a least resistance principle which humans use to release their charges, described by H7 in Table 2.
(v) Boxes (7), (12)-(13) and (11) represent the information input into our information processing center (Box (1)). Boxes (11) and (14) represent internal information inputs. Boxes (7), (12)-(13) represent external information inputs, which are explained in H8 in Table 2.
Comparison
Unsolicited InformationSolicited Information
External Problem Solving or Avoidance Justification
(14)
Figure 2: The Behavior Mechanism Table 1: Four Hypotheses of Brain Operation
Hypotheses Descriptions
H1 Circuit Pattern Hypothesis
Thoughts, concepts or ideas are represented by circuit patterns of the brain. The circuit patterns will be reinforced when the corresponding thoughts or ideas are repeated. Furthermore, the stronger the circuit patterns, the more easily the corresponding thoughts or ideas are retrieved in our thinking and decision making processes.
H2 Unlimited Capacity Hypothesis Practically every normal brain has the capacity to encode and store all thoughts, concepts and messages that one intends to.
H3 Efficient Restructuring
Hypothesis
The encoded thoughts, concepts and messages (H1) are organized and stored systematically as data bases for efficient retrieving. Furthermore, according to the dictation of attention they are continuously restructured so that relevant ones can be efficiently retrieved to release charges.
H4 Analogy/Association Hypothesis
The perception of new events, subjects, or ideas can be learned primarily by analogy and/or association with what is already known. When faced with a new event, subject, or idea, the brain first investigates its features and attributes in order to establish a relationship with what is already known by analogy and/or association. Once the right relationship has been established, the whole of the past knowledge (preexisting memory structure) is automatically brought to bear on the interpretation and understanding of the new event, subject or idea.
Table 2: Four Hypotheses of Mind Operation
Hypotheses Descriptions H5 Goal Setting and
State Evaluation Hypothesis
Each one of us has a set of goal functions and for each goal function we have an ideal state or equilibrium point to reach and maintain (goal setting). We continuously monitor, consciously or subconsciously, where we are relative to the ideal state or equilibrium point (state evaluation).
H6
Charge Structure and Attention
Allocation Hypothesis
Each event is related to a set of goal functions. When there is an unfavorable deviation of the perceived value from the ideal, each goal function will produce various levels of charge. The totality of the charges by all goal functions is called the charge structure and it can change dynamically. At any point in time, our attention will be paid to the event which has the most influence on our charge structure.
H7 Discharge Hypothesis
To release charges, we tend to select the action which yields the lowest remaining charge (the remaining charge is the resistance to the total discharge) and this is called the least resistance principle.
H8 Information Inputs Hypothesis
Humans have innate needs to gather external information.
Unless attention is paid, external information inputs may not be processed.
Note that there are four hypotheses (H1-H4 of Table 1) describing the information processing functions of the brain and four hypotheses (H5-H8 of Table 2) describing the general framework of our mind.
From the behavior mechanism of Figure 2 and the eight hypotheses, we notice that human’s behavioral system involves the following parameters: goal setting, state