Extended Operation as an Issue in Cognitive Architectures
In many cases, a given system may perform acceptably or even exceptionally
over a short period of time. However, since many of the agents and
architectures discussed in this document are being developed for
environments in which much longer running times are necessary for
the completion of a task (e.g., planetary expedition vehicles) or
for environments in which an agent will shift continuously from
task-to-task once initiated (e.g., a robot on a twenty-four hour
assembly line) the question of how the architecture behaves over
longer time scales becomes increasing central to a true measure
of its effectiveness.
Questions for extended operation include:
- What is the Mean-Time Between Failures for the system. Is the
failure hardware or software delimited?
- Is there a performance degradation over time? Almost as importantly,
is a performance decrease sub-linear, linear, or super-linear with respect
to increasing operation time?
- What happens to the world model over time? Specifically, are
previous world models and experiences in them learned and penetrable
(such as a form of episodic knowledge),
learned but impenetrable (such as some skill acquisition as
procedural knowledge) or discarded
without learning or recall of the event?
Architectures that include a discussion of this issue:
Go to the List of Common Issues.
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