640 research outputs found
Optimal equilibria of the best shot game
We consider any network environment in which the "best shot game" is played.
This is the case where the possible actions are only two for every node (0 and
1), and the best response for a node is 1 if and only if all her neighbors play
0. A natural application of the model is one in which the action 1 is the
purchase of a good, which is locally a public good, in the sense that it will
be available also to neighbors. This game typically exhibits a great
multiplicity of equilibria. Imagine a social planner whose scope is to find an
optimal equilibrium, i.e. one in which the number of nodes playing 1 is
minimal. To find such an equilibrium is a very hard task for any non-trivial
network architecture. We propose an implementable mechanism that, in the limit
of infinite time, reaches an optimal equilibrium, even if this equilibrium and
even the network structure is unknown to the social planner.Comment: submitted to JPE
Statics and dynamics of selfish interactions in distributed service systems
We study a class of games which model the competition among agents to access
some service provided by distributed service units and which exhibit congestion
and frustration phenomena when service units have limited capacity. We propose
a technique, based on the cavity method of statistical physics, to characterize
the full spectrum of Nash equilibria of the game. The analysis reveals a large
variety of equilibria, with very different statistical properties. Natural
selfish dynamics, such as best-response, usually tend to large-utility
equilibria, even though those of smaller utility are exponentially more
numerous. Interestingly, the latter actually can be reached by selecting the
initial conditions of the best-response dynamics close to the saturation limit
of the service unit capacities. We also study a more realistic stochastic
variant of the game by means of a simple and effective approximation of the
average over the random parameters, showing that the properties of the
average-case Nash equilibria are qualitatively similar to the deterministic
ones.Comment: 30 pages, 10 figure
Large deviations of cascade processes on graphs
Simple models of irreversible dynamical processes such as Bootstrap
Percolation have been successfully applied to describe cascade processes in a
large variety of different contexts. However, the problem of analyzing
non-typical trajectories, which can be crucial for the understanding of the
out-of-equilibrium phenomena, is still considered to be intractable in most
cases. Here we introduce an efficient method to find and analyze optimized
trajectories of cascade processes. We show that for a wide class of
irreversible dynamical rules, this problem can be solved efficiently on
large-scale systems
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The role of topology on the dynamics of the Naming Game
The Naming Game captures the essential features leading a population to agree on the use of a semiotic convention (or, more in general, an opinion). Consensus emerges through local negotiations between pairs of agents, in the absence of any central co-ordination. Thus, it is natural that topology, identifying the set of possible interactions, plays a central role in the dynamics of the model. Here, we review the role of different topological properties, pointing out that finite connectivity, combined with the small-world property, ensure the best performances in terms of memory usage and time to reach convergence
Containing epidemic outbreaks by message-passing techniques
The problem of targeted network immunization can be defined as the one of
finding a subset of nodes in a network to immunize or vaccinate in order to
minimize a tradeoff between the cost of vaccination and the final (stationary)
expected infection under a given epidemic model. Although computing the
expected infection is a hard computational problem, simple and efficient
mean-field approximations have been put forward in the literature in recent
years. The optimization problem can be recast into a constrained one in which
the constraints enforce local mean-field equations describing the average
stationary state of the epidemic process. For a wide class of epidemic models,
including the susceptible-infected-removed and the
susceptible-infected-susceptible models, we define a message-passing approach
to network immunization that allows us to study the statistical properties of
epidemic outbreaks in the presence of immunized nodes as well as to find
(nearly) optimal immunization sets for a given choice of parameters and costs.
The algorithm scales linearly with the size of the graph and it can be made
efficient even on large networks. We compare its performance with topologically
based heuristics, greedy methods, and simulated annealing
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Bootstrapping communication in language games
Semiotic dynamics is a fast growing field according to which language can be seen as an evolving and self-organizing system. In this paper we present a simple multi-agent framework able to account for the emergence of shared conventions in a population. Agents perform pairwise games and final consensus is reached without any outside control nor any global knowledge of the system. In particular we discuss how embedding the population in a non trivial interaction topology affects the behavior of the system and forces to carefully consider agents selection strategies. These results cast an interesting framework to address and study more complex issues in semiotic dynamics
Probabilistic seismic demand modeling of local level response parameters of an RC frame
Probabilistic methods to evaluate the seismic vulnerability of reinforced concrete (RC) frames are largely used in the context of performance based design and assessment, often describing the structural response using global engineering demand parameters (EDPs) such as the maximum interstory drift. While such EDPs are able to synthetically describe the structural behavior, the use of local EDPs is necessary to provide a more realistic and thorough description of failure mechanisms of low-ductility frames lacking seismic details. The objective of this paper is to investigate viable probabilistic seismic demand models of local EDPs, which may be used in developing fragility curves for the assessment of the low-ductility RC frames. The present work explores adequate regression models, probability distributions and uncertainty variation of the demand models. In addition, the adequacy of several ground motion intensity measures (IMs) to be used for predictive modeling of local EDPs is investigated. A realistic benchmark three-story RC frame representative of non-ductile buildings is used as a case study to identify key considerations
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Agreement dynamics on interaction networks with diverse topologies
We review the behavior of a recently introduced model of agreement dynamics, called the "Naming Game." This model describes the self-organized emergence of linguistic conventions and the establishment of simple communication systems in a population of agents with pairwise local interactions. The mechanisms of convergence towards agreement strongly depend on the network of possible interactions between the agents. In particular, the mean-field case in which all agents communicate with all the others is not efficient, since a large temporary memory is requested for the agents. On the other hand, regular lattice topologies lead to a fast local convergence but to a slow global dynamics similar to coarsening phenomena. The embedding of the agents in a small-world network represents an interesting tradeoff: a local consensus is easily reached, while the long-range links allow to bypass coarsening-like convergence. We also consider alternative adaptive strategies which can lead to faster global convergence
Vision-Based Structural Monitoring: Application to a Medium-Span Post-Tensioned Concrete Bridge under Vehicular Traffic
Video processing for structural monitoring has attracted much attention in recent years thanks to the possibility of measuring displacement time histories in the absence of stationary points close to the structure, using hardware that is simple to operate and with accessible costs. Experimental studies show a unanimous consensus on the potentialities of vision-based monitoring to provide accurate results that can be equivalent to those obtained from accelerometers and displacement transducers. However, past studies mostly involved steel bridges and footbridges while very few applications can be found for concrete bridges, characterised by a stiffer response with lower displacement magnitudes and different frequency contents of their dynamic behaviour. Accordingly, the attention of this experimental study is focused on the application of a vision-based structural monitoring system to a medium-span, post-tensioned, simply supported concrete bridge, a very common typology in many road networks. The objective is to provide evidence on the quality of the results that could be obtained using vision-based monitoring, understanding the role and influence on the accuracy of the measurements of various parameters relevant to the hardware settings and target geometry, highlighting possible difficulties, and providing practical recommendations to achieve optimal results
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