93,995 research outputs found
Universal Protocols for Information Dissemination Using Emergent Signals
We consider a population of agents which communicate with each other in a
decentralized manner, through random pairwise interactions. One or more agents
in the population may act as authoritative sources of information, and the
objective of the remaining agents is to obtain information from or about these
source agents. We study two basic tasks: broadcasting, in which the agents are
to learn the bit-state of an authoritative source which is present in the
population, and source detection, in which the agents are required to decide if
at least one source agent is present in the population or not.We focus on
designing protocols which meet two natural conditions: (1) universality, i.e.,
independence of population size, and (2) rapid convergence to a correct global
state after a reconfiguration, such as a change in the state of a source agent.
Our main positive result is to show that both of these constraints can be met.
For both the broadcasting problem and the source detection problem, we obtain
solutions with a convergence time of rounds, w.h.p., from any
starting configuration. The solution to broadcasting is exact, which means that
all agents reach the state broadcast by the source, while the solution to
source detection admits one-sided error on a -fraction of the
population (which is unavoidable for this problem). Both protocols are easy to
implement in practice and have a compact formulation.Our protocols exploit the
properties of self-organizing oscillatory dynamics. On the hardness side, our
main structural insight is to prove that any protocol which meets the
constraints of universality and of rapid convergence after reconfiguration must
display a form of non-stationary behavior (of which oscillatory dynamics are an
example). We also observe that the periodicity of the oscillatory behavior of
the protocol, when present, must necessarily depend on the number ^\\# X of
source agents present in the population. For instance, our protocols inherently
rely on the emergence of a signal passing through the population, whose period
is \Theta(\log \frac{n}{^\\# X}) rounds for most starting configurations. The
design of clocks with tunable frequency may be of independent interest, notably
in modeling biological networks
Policies for allocation of information in task-oriented groups: elitism and egalitarianism outperform welfarism
Communication or influence networks are probably the most controllable of all
factors that are known to impact on the problem-solving capability of
task-forces. In the case connections are costly, it is necessary to implement a
policy to allocate them to the individuals. Here we use an agent-based model to
study how distinct allocation policies affect the performance of a group of
agents whose task is to find the global maxima of NK fitness landscapes. Agents
cooperate by broadcasting messages informing on their fitness and use this
information to imitate the fittest agent in their influence neighborhoods. The
larger the influence neighborhood of an agent, the more links, and hence
information, the agent receives. We find that the elitist policy in which
agents with above-average fitness have their influence neighborhoods amplified,
whereas agents with below-average fitness have theirs deflated, is optimal for
smooth landscapes, provided the group size is not too small. For rugged
landscapes, however, the elitist policy can perform very poorly for certain
group sizes. In addition, we find that the egalitarian policy, in which the
size of the influence neighborhood is the same for all agents, is optimal for
both smooth and rugged landscapes in the case of small groups. The welfarist
policy, in which the actions of the elitist policy are reversed, is always
suboptimal, i.e., depending on the group size it is outperformed by either the
elitist or the egalitarian policies
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