963 research outputs found
Let Cognitive Radios Imitate: Imitation-based Spectrum Access for Cognitive Radio Networks
In this paper, we tackle the problem of opportunistic spectrum access in
large-scale cognitive radio networks, where the unlicensed Secondary Users (SU)
access the frequency channels partially occupied by the licensed Primary Users
(PU). Each channel is characterized by an availability probability unknown to
the SUs. We apply evolutionary game theory to model the spectrum access problem
and develop distributed spectrum access policies based on imitation, a behavior
rule widely applied in human societies consisting of imitating successful
behavior. We first develop two imitation-based spectrum access policies based
on the basic Proportional Imitation (PI) rule and the more advanced Double
Imitation (DI) rule given that a SU can imitate any other SUs. We then adapt
the proposed policies to a more practical scenario where a SU can only imitate
the other SUs operating on the same channel. A systematic theoretical analysis
is presented for both scenarios on the induced imitation dynamics and the
convergence properties of the proposed policies to an imitation-stable
equilibrium, which is also the -optimum of the system. Simple,
natural and incentive-compatible, the proposed imitation-based spectrum access
policies can be implemented distributedly based on solely local interactions
and thus is especially suited in decentralized adaptive learning environments
as cognitive radio networks
The lower convergence tendency of imitators compared to best responders
Imitation is widely observed in nature and often used to model populations of decision-making agents, but it is not yet known under what conditions a network of imitators will reach a state where they are satisfied with their decisions. We show that every network in which agents imitate the best performing strategy in their neighborhood will reach an equilibrium in finite time, provided that all agents are opponent coordinating, i.e., earn a higher payoff if their opponent plays the same strategy as they do. It follows that any non-convergence observed in imitative networks is not necessarily a result of population heterogeneity nor special network topology, but rather must be caused by other factors such as the presence of non-opponent-coordinating agents. To strengthen this result, we show that large classes of imitative networks containing non-opponent-coordinating agents never equilibrate even when the population is homogeneous. Comparing to best-response dynamics where equilibration is guaranteed for every network of homogeneous agents playing 2 × 2 matrix games, our results imply that networks of imitators have a lower equilibration tendency
From Social Simulation to Integrative System Design
As the recent financial crisis showed, today there is a strong need to gain
"ecological perspective" of all relevant interactions in
socio-economic-techno-environmental systems. For this, we suggested to set-up a
network of Centers for integrative systems design, which shall be able to run
all potentially relevant scenarios, identify causality chains, explore feedback
and cascading effects for a number of model variants, and determine the
reliability of their implications (given the validity of the underlying
models). They will be able to detect possible negative side effect of policy
decisions, before they occur. The Centers belonging to this network of
Integrative Systems Design Centers would be focused on a particular field, but
they would be part of an attempt to eventually cover all relevant areas of
society and economy and integrate them within a "Living Earth Simulator". The
results of all research activities of such Centers would be turned into
informative input for political Decision Arenas. For example, Crisis
Observatories (for financial instabilities, shortages of resources,
environmental change, conflict, spreading of diseases, etc.) would be connected
with such Decision Arenas for the purpose of visualization, in order to make
complex interdependencies understandable to scientists, decision-makers, and
the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c
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