Deliberate Construction in Parallel Constraint Satisfaction

deliberativeimagesAccording to Glockner and Betsch, deliberate constructions (DCs) are the opportunity for the deliberate/analytical system to provide input into decision making. The Parallel Constraint Satisfaction rule holistically considers the information contained in a network. The network consists of all pieces of information that comprise the decision problem (cues, goals, options, evaluations, etc.). In many mundane situations, the constitution of the network does not require any sort of active information search. Relevant features of the environment and currently activated memory entries provide the input to the network. Glockner and Betsch refer to the network installed spontaneously when encountering a decision situation as the primary network.   Deliberate processes are activated if the consistency of a resulting mental representation is below a threshold θ. I think this is interesting because it is the intuitive/automatic system requiring coherency of itself. Typically, we think of the deliberate/analytical system as being rational and coherent, while the intuitive system requires correspondence.  In this situation, the intuitive/automatic system finds answers that are not consistent, incoherent, and thus seeks input from the deliberate/analytical system.

In other situations, the primary network is nearly empty (it still contains goals and representations of the decision problem).  The secondary network will be formed immediately upon encountering the task, and the individual will first decide how to gather or produce information.

Secondary Network

Glockner and Betsch refer to this secondary network as activating potential deliberate “construction mechanisms” which in turn can support the consistency maximization in the primary network.  In the simplest case, deliberate/analytical processes are used to gather or produce (additional) information – e.g., on the basis of mathematical analyses – and therefore to enrich the network. Moreover, deliberate processes can be used for a temporal change of the network structure, for example to simulate different interpretations of the situation.

The secondary network functions as an aiding system in order to help the primary network do its job. Glockner and Betsch note that the secondary network impacts option decisions in an indirect fashion by providing or changing information. The decisions made in the secondary network are made among strategies of search, information generation and change. Apart from their different functions, the two networks obey the same principles of consistency maximizing.

Types of Deliberate Constructions
The deliberate constructions might be “Search for information in the environment according to the importance of cues across options” or “consider all the outcomes of an option before considering a further option.” Production strategies refer to both rehearsal strategies for accessing information from memory and rules of inference and deduction. The latter may help to anticipate the risk of future events. Strategies of information change involve a reinterpretation of the relations among goals, options and behaviors. A routine decision maker might realize that the world has changed and that the routine option no longer promotes his or her goals. Due to the prior success of the routine, the connection between the goals and the behavior are positive. By virtue of active mental control,  the decision maker may adapt the weights temporarily. Like options on the behavioral level, DC strategies can be learned and become routinized. Over the course of their lifetime, deciders will eventually accumulate a set of DC routines that suit specific types of decision situations. These routines need not be learned via first-hand experience. They can also be handed down via communication and instruction. Glockner and Betsch provide the example of teaching their MA and PhD students to use the PsycINFO search engine before deciding which line of research they should pursue further. In new situations, deciders may remain focused on generalized strategies for information production, and these generalized strategies may remain comparatively stable within a person.  Individuals differ regarding the scrutiny, the focus of attention and the direction in considering information. Some people generally prefer to consider a larger amount of information and to explore the problem space more thoroughly than others (maximizers and satisficers).  Some people prefer to focus on the experiential or affective level, whereas others are more responsive to the  cognitive level of information.  Moreover, information search may generally be biased towards the confirmation rather than disconfirmation of a starting hypothesis.
If individuals start with the hypothesis that option A might be better than option B (e.g., due to the fact that A performed well in the past), they might reveal a tendency to search for evidence that favors A or challenges B.
Choosing a DC strategy
This follows the same principle as decision making among choice options.   The main goal is to help the primary network to find a solution, which means that the utility of a strategy depends on the extent to which it helps establish consistency in the primary network. Other goals relating to accuracy and effort complement the motivational part of the secondary network. Again, the content and structure of the network are strongly determined by prior experience and learning.  Glockner and Betsch assume that after a DC candidate is chosen and implemented, the output of these operations (e.g., new information) is fed into the primary network. Secondary processes (network formation, implementation of DC operations) will operate until an acceptable level of consistency is installed in the primary network.

Past experiences can change the structure of weights in the network reflecting prior associated learning. Future experiences will provide the decision maker with feedback. One consequence of feedback learning is that individuals establish a repertoire of routines both on the level of options and on the level of DC strategies (e.g., search routines) There are also results from expertise research that are informative concerning the question when DCs are activated.  Experts tend to have more knowledge about knowledge and this should lower the threshold for initiating DCs. Experts should also require a higher consistency/coherence in their network before coming to a decision.

Glockner A, Betsch T., “Modeling option and strategy choices with connectionist networks: Towards an integrative model of automatic and deliberate decision
making.”  Judgment and Decision Making, Vol. 3, No. 3, March 2008, pp. 215–228.

Herwig B, Glockner A. “Experts and Decision Making: First Steps Towards a Unifying Theory of Decision Making in Novices, Intermediates and Experts,”  published by the Max Planck Institute for Research on Collective Goods, Bonn 2009/2,

 

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