8 research outputs found
Commitment versus persuasion in the three-party constrained voter model
In the framework of the three-party constrained voter model, where voters of
two radical parties (A and B) interact with "centrists" (C and Cz), we study
the competition between a persuasive majority and a committed minority. In this
model, A's and B's are incompatible voters that can convince centrists or be
swayed by them. Here, radical voters are more persuasive than centrists, whose
sub-population consists of susceptible agents C and a fraction zeta of centrist
zealots Cz. Whereas C's may adopt the opinions A and B with respective rates
1+delta_A and 1+delta_B (with delta_A>=delta_B>0), Cz's are committed
individuals that always remain centrists. Furthermore, A and B voters can
become (susceptible) centrists C with a rate 1. The resulting competition
between commitment and persuasion is studied in the mean field limit and for a
finite population on a complete graph. At mean field level, there is a
continuous transition from a coexistence phase when
zeta=
Delta_c. In a finite population of size N, demographic fluctuations lead to
centrism consensus and the dynamics is characterized by the mean consensus time
tau. Because of the competition between commitment and persuasion, here
consensus is reached much slower (zeta=Delta_c) than
in the absence of zealots (when tau\simN). In fact, when zeta<Delta_c and there
is an initial minority of centrists, the mean consensus time asymptotically
grows as tau\simN^{-1/2} e^{N gamma}, where gamma is determined. The dynamics
is thus characterized by a metastable state where the most persuasive voters
and centrists coexist when delta_A>delta_B, whereas all species coexist when
delta_A=delta_B. When zeta>=Delta_c and the initial density of centrists is
low, one finds tau\simln N (when N>>1). Our analytical findings are
corroborated by stochastic simulations.Comment: 25 pages, 6 figures. Final version for the Journal of Statistical
Physics (special issue on the "applications of statistical mechanics to
social phenomena"
Crowd computing as a cooperation problem: an evolutionary approach
Cooperation is one of the socio-economic issues that has received more attention from the physics community. The problem has been mostly considered by studying games such as the Prisoner's Dilemma or the Public Goods Game. Here, we take a step forward by studying cooperation in the context of crowd computing. We introduce a model loosely based on Principal-agent theory in which people (workers) contribute to the solution of a distributed problem by computing answers and reporting to the problem proposer (master). To go beyond classical approaches involving the concept of Nash equilibrium, we work on an evolutionary framework in which both the master and the workers update their behavior through reinforcement learning. Using a Markov chain approach, we show theoretically that under certain----not very restrictive-conditions, the master can ensure the reliability of the answer resulting of the process. Then, we study the model by numerical simulations, finding that convergence, meaning that the system reaches a point in which it always produces reliable answers, may in general be much faster than the upper bounds given by the theoretical calculation. We also discuss the effects of the master's level of tolerance to defectors, about which the theory does not provide information. The discussion shows that the system works even with very large tolerances. We conclude with a discussion of our results and possible directions to carry this research further.This work is supported by the Cyprus Research Promotion Foundation grant TE/HPO/0609(BE)/05, the National Science Foundation (CCF-0937829, CCF-1114930), Comunidad de Madrid grant S2009TIC-1692 and MODELICO-CM, Spanish MOSAICO, PRODIEVO and RESINEE grants and MICINN grant TEC2011-29688-C02-01, and National Natural Science Foundation of China grant 61020106002.Publicad
Hierarchy of Scales in Language Dynamics
Methods and insights from statistical physics are finding an increasing variety of applications where one seeks to understand the emergent properties of a complex interacting system. One such area concerns the dynamics of language at a variety of levels of description, from the behaviour of individual agents learning simple artificial languages from each other, up to changes in the structure of languages shared by large groups of speakers over historical timescales. In this Colloquium, we survey a hierarchy of scales at which language and linguistic behaviour can be described, along with the main progress in understanding that has been made at each of them − much of which has come from the statistical physics community. We argue that future developments may arise by linking the different levels of the hierarchy together in a more coherent fashion, in particular where this allows more effective use of rich empirical data sets
Special issue on second generation plasma accelerators
The above quotation is not an advertisement for an automobile magazine; rather it is one of the highlights of the experimental results presented at a recent workshop in Kardamyli, Greece and in this Special Issue. This is the second Special Issue of the IEEE TRANSACTIONS ON PLASMA SCIENCE devoted to the topic of plasma accelerators. The first one was over nine years ago!’ A brief comparison of these ‘T. C. Katsouleas, Ed., IEEE Tram Plasma Sci., vol. PS-15, pp. 85-255, 1987. two issues serves to summarize the tremendous progress in the field over this period