31,615 research outputs found
Using synchronous Boolean networks to model several phenomena of collective behavior
In this paper, we propose an approach for modeling and analysis of a number
of phenomena of collective behavior. By collectives we mean multi-agent systems
that transition from one state to another at discrete moments of time. The
behavior of a member of a collective (agent) is called conforming if the
opinion of this agent at current time moment conforms to the opinion of some
other agents at the previous time moment. We presume that at each moment of
time every agent makes a decision by choosing from the set {0,1} (where
1-decision corresponds to action and 0-decision corresponds to inaction). In
our approach we model collective behavior with synchronous Boolean networks. We
presume that in a network there can be agents that act at every moment of time.
Such agents are called instigators. Also there can be agents that never act.
Such agents are called loyalists. Agents that are neither instigators nor
loyalists are called simple agents. We study two combinatorial problems. The
first problem is to find a disposition of instigators that in several time
moments transforms a network from a state where a majority of simple agents are
inactive to a state with a majority of active agents. The second problem is to
find a disposition of loyalists that returns the network to a state with a
majority of inactive agents. Similar problems are studied for networks in which
simple agents demonstrate the contrary to conforming behavior that we call
anticonforming. We obtained several theoretical results regarding the behavior
of collectives of agents with conforming or anticonforming behavior. In
computational experiments we solved the described problems for randomly
generated networks with several hundred vertices. We reduced corresponding
combinatorial problems to the Boolean satisfiability problem (SAT) and used
modern SAT solvers to solve the instances obtained
Applying Formal Methods to Networking: Theory, Techniques and Applications
Despite its great importance, modern network infrastructure is remarkable for
the lack of rigor in its engineering. The Internet which began as a research
experiment was never designed to handle the users and applications it hosts
today. The lack of formalization of the Internet architecture meant limited
abstractions and modularity, especially for the control and management planes,
thus requiring for every new need a new protocol built from scratch. This led
to an unwieldy ossified Internet architecture resistant to any attempts at
formal verification, and an Internet culture where expediency and pragmatism
are favored over formal correctness. Fortunately, recent work in the space of
clean slate Internet design---especially, the software defined networking (SDN)
paradigm---offers the Internet community another chance to develop the right
kind of architecture and abstractions. This has also led to a great resurgence
in interest of applying formal methods to specification, verification, and
synthesis of networking protocols and applications. In this paper, we present a
self-contained tutorial of the formidable amount of work that has been done in
formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial
Visualizing and Interacting with Concept Hierarchies
Concept Hierarchies and Formal Concept Analysis are theoretically well
grounded and largely experimented methods. They rely on line diagrams called
Galois lattices for visualizing and analysing object-attribute sets. Galois
lattices are visually seducing and conceptually rich for experts. However they
present important drawbacks due to their concept oriented overall structure:
analysing what they show is difficult for non experts, navigation is
cumbersome, interaction is poor, and scalability is a deep bottleneck for
visual interpretation even for experts. In this paper we introduce semantic
probes as a means to overcome many of these problems and extend usability and
application possibilities of traditional FCA visualization methods. Semantic
probes are visual user centred objects which extract and organize reduced
Galois sub-hierarchies. They are simpler, clearer, and they provide a better
navigation support through a rich set of interaction possibilities. Since probe
driven sub-hierarchies are limited to users focus, scalability is under control
and interpretation is facilitated. After some successful experiments, several
applications are being developed with the remaining problem of finding a
compromise between simplicity and conceptual expressivity
Bounds on the Average Sensitivity of Nested Canalizing Functions
Nested canalizing Boolean (NCF) functions play an important role in
biological motivated regulative networks and in signal processing, in
particular describing stack filters. It has been conjectured that NCFs have a
stabilizing effect on the network dynamics. It is well known that the average
sensitivity plays a central role for the stability of (random) Boolean
networks. Here we provide a tight upper bound on the average sensitivity for
NCFs as a function of the number of relevant input variables. As conjectured in
literature this bound is smaller than 4/3 This shows that a large number of
functions appearing in biological networks belong to a class that has very low
average sensitivity, which is even close to a tight lower bound.Comment: revised submission to PLOS ON
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