"Developing cognitive architecture for modelling and simulation
of cognition and error in complex tasks" - paper frame
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Grant, S. (unpublished)
Developing cognitive architecture for modelling and simulations
of cognition and error in complex tasks.
Paper presented at a meeting of the RoHMI project,
Valenciennes, February 1996
European Commission, Joint Research Centre
Institute for Systems Engineering and Informatics
A cognitive architecture embodies the more general structures
and mechanisms out of which could be made a model of individual
cognition in a certain situation. The space of models and architectures
has a number of dimensions, including: dependence on domain; level
of specification; and extent of coverage of different phenomena.
Cognitive architectures can be assessed in terms of their ability
to support the construction of models and simulations of cognition
and error. ACT-R is an example of a moderately specified architecture,
in which one can build such simulation models. There are some
features that are important in the study of complex tasks that
ACT-R is not well-adapted to modelling: included among these are
the modelling of certain types of error. ACT-R does not by itself
strongly constrain a model to be psychologically plausible - that
is left to the person building the model. The architecture derived
from COSIMO is open to extension and improvement in a similar
Relevant work towards developing cognitive architectures for modelling
cognition and error in complex tasks can include on the one hand
generalizing from domain-specific models, based on results from
the study of cognition and errors in real complex tasks, and on
the other hand hypothesizing more detailed computational mechanisms
for the implementation of general error-prone cognitive abilities,
which may be pointed out by cognitive psychology. It would appear
to be best if these two approaches progressed hand in hand, since
they are two sides of the same enterprise.
2.1 The analogy with architecture of physical structures
2.2 Models and simulations
2.3 The status of cognitive models and architecture
3.1 Dimensions and development motives
3.2 The interplay of architectures and models
5.1 An incremental approach
5.2 Approach from the real world towards generality
5.3 Approach from theory towards cognitive relevance
5.4 Balanced approach
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