1,165 research outputs found
Entanglement between Demand and Supply in Markets with Bandwagon Goods
Whenever customers' choices (e.g. to buy or not a given good) depend on
others choices (cases coined 'positive externalities' or 'bandwagon effect' in
the economic literature), the demand may be multiply valued: for a same posted
price, there is either a small number of buyers, or a large one -- in which
case one says that the customers coordinate. This leads to a dilemma for the
seller: should he sell at a high price, targeting a small number of buyers, or
at low price targeting a large number of buyers? In this paper we show that the
interaction between demand and supply is even more complex than expected,
leading to what we call the curse of coordination: the pricing strategy for the
seller which aimed at maximizing his profit corresponds to posting a price
which, not only assumes that the customers will coordinate, but also lies very
near the critical price value at which such high demand no more exists. This is
obtained by the detailed mathematical analysis of a particular model formally
related to the Random Field Ising Model and to a model introduced in social
sciences by T C Schelling in the 70's.Comment: Updated version, accepted for publication, Journal of Statistical
Physics, online Dec 201
Byzantine Gathering in Networks
This paper investigates an open problem introduced in [14]. Two or more
mobile agents start from different nodes of a network and have to accomplish
the task of gathering which consists in getting all together at the same node
at the same time. An adversary chooses the initial nodes of the agents and
assigns a different positive integer (called label) to each of them. Initially,
each agent knows its label but does not know the labels of the other agents or
their positions relative to its own. Agents move in synchronous rounds and can
communicate with each other only when located at the same node. Up to f of the
agents are Byzantine. A Byzantine agent can choose an arbitrary port when it
moves, can convey arbitrary information to other agents and can change its
label in every round, in particular by forging the label of another agent or by
creating a completely new one.
What is the minimum number M of good agents that guarantees deterministic
gathering of all of them, with termination?
We provide exact answers to this open problem by considering the case when
the agents initially know the size of the network and the case when they do
not. In the former case, we prove M=f+1 while in the latter, we prove M=f+2.
More precisely, for networks of known size, we design a deterministic algorithm
gathering all good agents in any network provided that the number of good
agents is at least f+1. For networks of unknown size, we also design a
deterministic algorithm ensuring the gathering of all good agents in any
network but provided that the number of good agents is at least f+2. Both of
our algorithms are optimal in terms of required number of good agents, as each
of them perfectly matches the respective lower bound on M shown in [14], which
is of f+1 when the size of the network is known and of f+2 when it is unknown
Robustness of Cooperation in the Evolutionary Prisoner's Dilemma on Complex Networks
Recent studies on the evolutionary dynamics of the Prisoner's Dilemma game in
scale-free networks have demonstrated that the heterogeneity of the network
interconnections enhances the evolutionary success of cooperation. In this
paper we address the issue of how the characterization of the asymptotic states
of the evolutionary dynamics depends on the initial concentration of
cooperators. We find that the measure and the connectedness properties of the
set of nodes where cooperation reaches fixation is largely independent of
initial conditions, in contrast with the behavior of both the set of nodes
where defection is fixed, and the fluctuating nodes. We also check for the
robustness of these results when varying the degree heterogeneity along a
one-parametric family of networks interpolating between the class of
Erdos-Renyi graphs and the Barabasi-Albert networks.Comment: 18 pages, 6 figures, revised version accepted for publication in New
Journal of Physics (2007
Nonequilibrium phase transition due to social group isolation
We introduce a simple model of a growing system with competing
communities. The model corresponds to the phenomenon of defeats suffered by
social groups living in isolation. A nonequilibrium phase transition is
observed when at critical time the first isolated cluster occurs. In the
one-dimensional system the volume of the new phase, i.e. the number of the
isolated individuals, increases with time as . For a large number
of possible communities the critical density of filled space equals to where is the system size. A similar transition is observed
for Erd\H{o}s-R\'{e}nyi random graphs and Barab\'{a}si-Albert scale-free
networks. Analytic results are in agreement with numerical simulations.Comment: 5 pages, 4 figure
Heterogeneous out-of-equilibrium nonlinear q-voter model with zealotry
We study the dynamics of the out-of-equilibrium nonlinear q-voter model with two types of susceptible voters and zealots, introduced in [EPL 113, 48001 (2016)]. In this model, each individual supports one of two parties and is either a susceptible voter of type q1 or q2, or is an inflexible zealot. At each time step, a qi-susceptible voter (i = 1, 2) consults a group of qi neighbors and adopts their opinion if all group members agree, while zealots are inflexible and never change their opinion. This model violates detailed balance whenever q1 6= q2 and is characterized by two distinct regimes of low and high density of zealotry. Here, by combining analytical and numerical methods, we investigate the non-equilibrium stationary state of the system in terms of its probability distribution, non-vanishing currents and unequal-time two-point correlation functions. We also study the switching times properties of the model by exploiting an approximate mapping onto the model of [Phys. Rev. E 92, 012803 (2015)] that satisfies the detailed balance, and we outline some properties of the model near criticality
Game Theoretical Interactions of Moving Agents
Game theory has been one of the most successful quantitative concepts to
describe social interactions, their strategical aspects, and outcomes. Among
the payoff matrix quantifying the result of a social interaction, the
interaction conditions have been varied, such as the number of repeated
interactions, the number of interaction partners, the possibility to punish
defective behavior etc. While an extension to spatial interactions has been
considered early on such as in the "game of life", recent studies have focussed
on effects of the structure of social interaction networks.
However, the possibility of individuals to move and, thereby, evade areas
with a high level of defection, and to seek areas with a high level of
cooperation, has not been fully explored so far. This contribution presents a
model combining game theoretical interactions with success-driven motion in
space, and studies the consequences that this may have for the degree of
cooperation and the spatio-temporal dynamics in the population. It is
demonstrated that the combination of game theoretical interactions with motion
gives rise to many self-organized behavioral patterns on an aggregate level,
which can explain a variety of empirically observed social behaviors
Spatial interactions in agent-based modeling
Agent Based Modeling (ABM) has become a widespread approach to model complex
interactions. In this chapter after briefly summarizing some features of ABM
the different approaches in modeling spatial interactions are discussed.
It is stressed that agents can interact either indirectly through a shared
environment and/or directly with each other. In such an approach, higher-order
variables such as commodity prices, population dynamics or even institutions,
are not exogenously specified but instead are seen as the results of
interactions. It is highlighted in the chapter that the understanding of
patterns emerging from such spatial interaction between agents is a key problem
as much as their description through analytical or simulation means.
The chapter reviews different approaches for modeling agents' behavior,
taking into account either explicit spatial (lattice based) structures or
networks. Some emphasis is placed on recent ABM as applied to the description
of the dynamics of the geographical distribution of economic activities, - out
of equilibrium. The Eurace@Unibi Model, an agent-based macroeconomic model with
spatial structure, is used to illustrate the potential of such an approach for
spatial policy analysis.Comment: 26 pages, 5 figures, 105 references; a chapter prepared for the book
"Complexity and Geographical Economics - Topics and Tools", P. Commendatore,
S.S. Kayam and I. Kubin, Eds. (Springer, in press, 2014
A measure of individual role in collective dynamics
Identifying key players in collective dynamics remains a challenge in several
research fields, from the efficient dissemination of ideas to drug target
discovery in biomedical problems. The difficulty lies at several levels: how to
single out the role of individual elements in such intermingled systems, or
which is the best way to quantify their importance. Centrality measures
describe a node's importance by its position in a network. The key issue
obviated is that the contribution of a node to the collective behavior is not
uniquely determined by the structure of the system but it is a result of the
interplay between dynamics and network structure. We show that dynamical
influence measures explicitly how strongly a node's dynamical state affects
collective behavior. For critical spreading, dynamical influence targets nodes
according to their spreading capabilities. For diffusive processes it
quantifies how efficiently real systems may be controlled by manipulating a
single node.Comment: accepted for publication in Scientific Report
Ripple Texturing of Suspended Graphene Atomic Membranes
Graphene is the nature's thinnest elastic membrane, with exceptional
mechanical and electrical properties. We report the direct observation and
creation of one-dimensional (1D) and 2D periodic ripples in suspended graphene
sheets, using spontaneously and thermally induced longitudinal strains on
patterned substrates, with control over their orientations and wavelengths. We
also provide the first measurement of graphene's thermal expansion coefficient,
which is anomalously large and negative, ~ -7x10^-6 K^-1 at 300K. Our work
enables novel strain-based engineering of graphene devices.Comment: 15 pages, 4 figure
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