Christoph Jung and Christian Gerber
Abstract Resources as a Modelling Device in the Bounded Optimal Society
The bounded rational agent is nowadays a widely agreed and well
understood paradigm in Cognitive Science, especially in
Artificial
Intelligence (AI). Yet, the generalization of theories and their
practical
implications, such as of bounded optimality, to societies of
agents has not yet been investigated systematically. We address
these aspects
from the perspective of Distributed Artificial Intelligence (DAI)
by
developing a hierarchical resource adaption scheme. This scheme
links
the micro-level of a hybrid and layered agent
architecture
to the macro-level of the corresponding society. Each of the
social and
individual-agent decision stages integrates the complementary benefits
of
simple (one-step) and complex (about a sequence of steps)
decision making. Both mechanisms employ the representational device of
abstract resources as a unified representation of quantitative
environmental and architectural constraints. Besides their practical
aspects in
optimising agent applications, we propose abstract resources as a
modelling
tool for social (on the macro-level) as well as the cognitive sciences
(the
micro-level).