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Parallel Constraint
Satisfaction Processes
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Parallel Constraint Satisfaction Processes (PCSP) is a model that integrates the fastest
growing research areas in the study of the mind; Connectionism, neural networks, and
parallel distributed processing models.
Dynamic model of attitude
This model integrates these three areas to propose a holistic explanation for an individual’s
response to cognitive dissonance. It models an explanation of the dynamic structure of
attitudes and the attitude change involved in cognitive dissonance theory. PCSP posits that
beliefs impose constraints on other beliefs, and conditions can either constrain or make
salient different aspects of one’s beliefs. Attitudes and beliefs are therefore changeable, due
to trying to satisfactorily fit with the various constraints of circumstances as well as adapt to
the constantly evolving truths in life. It is not an alternative to the theory but rather a model
that incorporates the many facets of cognitive dissonance theory. Cognitive dissonance theory
centers mainly on:

Cognition

Self-concept

Social identity
Human beings may give greater importance to one of these areas but no single factor will be
the sole influence. The different theories are probably all accurate given the right time, the
right place, and the right individual, therefore an integrated more holistic model may better
explain the reasons for attitude/behavior inconsistency and the change of attitude following
cognitive dissonance.
Gestalt psychology and parallel constraint satisfaction processes
Researchers (Read 1991) have found within Gestalt psychology an integrated model of
explaining attitude change that incorporates neuroscientific and social psychological
concepts. Theories of cognitive dissonance as well as its alternatives are based on the
assumption that the attitudes and beliefs one holds are fixed entities. Recently psychologists
have progressed from categorizing psychological phenomena as static, to recognizing the
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dynamic aspects that vary with different contexts. The concept of neural network models uses
the Gestalt principle of totality to explain social, emotional and cognitive tendencies.
In a feedback or parallel constraint satisfaction network, activation passes around
symmetrically connected nodes until the activation of all the nodes asymptotes or "relaxes"
into a state that satisfies the constraints among the nodes. This process allows for the
integration of a number of different sources of information in parallel.
Social psychology and parallel constraint satisfaction processes
Parallel Constraint Satisfaction Processes can be applied to three broad areas in social
psychology:

Impression formation and causal attribution

Cognitive consistency

Goal-directed behavior.
This approach revealed that some phenomena that seem unexpected or counterintuitive are in
actuality due to the normal functioning of the cognitive system. For example, Shultz and
Lepper (1996) noted that in thinking about cognitive dissonance in terms of parallel
constraint satisfaction processes, it becomes clear that cognitive consistency phenomena—
such as those studied by dissonance researchers—are not the result of atypical or unusual
cognitive processes but rather are the direct result of normal cognitive functioning.
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