195 research outputs found
Universality of Zipf's Law
Zipf's law is the most common statistical distribution displaying scaling
behavior. Cities, populations or firms are just examples of this seemingly
universal law. Although many different models have been proposed, no general
theoretical explanation has been shown to exist for its universality. Here we
show that Zipf's law is, in fact, an inevitable outcome of a very general class
of stochastic systems. Borrowing concepts from Algorithmic Information Theory,
our derivation is based on the properties of the symbolic sequence obtained
through successive observations over a system with an unbounded number of
possible states. Specifically, we assume that the complexity of the description
of the system provided by the sequence of observations is the one expected for
a system evolving to a stable state between order and disorder. This result is
obtained from a small set of mild, physically relevant assumptions. The general
nature of our derivation and its model-free basis would explain the ubiquity of
such a law in real systems.Comment: 11 Pages, 2 figure
Inertial measurent units and their application to mobile robot localization
Resumen del trabajo presentado al seminario celebrado en el Instituto de Robótica e Informática Industrial (IRII-CSIC-UPC) el 6 de marzo de 2014.Peer Reviewe
Detection of the elite structure in a virtual multiplex social system by means of a generalized -core
Elites are subgroups of individuals within a society that have the ability
and means to influence, lead, govern, and shape societies. Members of elites
are often well connected individuals, which enables them to impose their
influence to many and to quickly gather, process, and spread information. Here
we argue that elites are not only composed of highly connected individuals, but
also of intermediaries connecting hubs to form a cohesive and structured
elite-subgroup at the core of a social network. For this purpose we present a
generalization of the -core algorithm that allows to identify a social core
that is composed of well-connected hubs together with their `connectors'. We
show the validity of the idea in the framework of a virtual world defined by a
massive multiplayer online game, on which we have complete information of
various social networks. Exploiting this multiplex structure, we find that the
hubs of the generalized -core identify those individuals that are high
social performers in terms of a series of indicators that are available in the
game. In addition, using a combined strategy which involves the generalized
-core and the recently introduced -core, the elites of the different
'nations' present in the game are perfectly identified as modules of the
generalized -core. Interesting sudden shifts in the composition of the elite
cores are observed at deep levels. We show that elite detection with the
traditional -core is not possible in a reliable way. The proposed method
might be useful in a series of more general applications, such as community
detection.Comment: 13 figures, 3 tables, 19 pages. Accepted for publication in PLoS ON
Map-based localization for urban service mobile robotics
Mobile robotics research is currently interested on exporting autonomous navigation results achieved in indoor environments, to more challenging environments, such as, for instance, urban pedestrian areas. Developing mobile robots with autonomous navigation capabilities in such urban environments supposes a basic requirement for a upperlevel service set that could be provided to an users community. However, exporting indoor techniques to outdoor urban pedestrian scenarios is not evident due to the larger size of the environment, the dynamism of the scene due to
pedestrians and other moving obstacles, the sunlight conditions, and the high presence of three dimensional elements such as ramps, steps, curbs or holes. Moreover, GPS-based mobile robot localization has demonstrated insufficient
performance for robust long-term navigation in urban environments.
One of the key modules within autonomous navigation is localization. If localization supposes an a priori map, even if it is not a complete model of the environment, localization is called map-based. This assumption is realistic since current
trends of city councils are on building precise maps of their cities, specially of the most interesting places such as city downtowns. Having robots localized within a map allows for a high-level planning and monitoring, so that robots can
achieve goal points expressed on the map, by following in a deliberative way a previously planned route.
This thesis deals with the mobile robot map-based localization issue in urban pedestrian areas. The thesis approach uses the particle filter algorithm, a well-known and widely used probabilistic and recursive method for data fusion and state estimation. The main contributions of the thesis are divided on four aspects: (1) long-term experiments of mobile robot 2D and 3D position tracking in real urban pedestrian scenarios within a full autonomous navigation framework, (2) developing a fast and accurate technique to compute on-line range observation models in 3D environments, a basic step required by the real-time performance of the developed particle filter, (3) formulation of a particle filter that integrates asynchronous data streams and (4) a theoretical proposal to solve the global localization problem in an active and cooperative way, defining cooperation as either information sharing among the robots or planning joint actions to solve a common goal.Actualment, la recerca en robòtica mòbil té un interés creixent en exportar els resultats de navegació autònoma
aconseguits en entorns interiors cap a d'altres tipus d'entorns més exigents, com, per exemple, les àrees urbanes
peatonals. Desenvolupar capacitats de navegació autònoma en aquests entorns urbans és un requisit bàsic per poder
proporcionar un conjunt de serveis de més alt nivell a una comunitat d'usuaris. Malgrat tot, exportar les tècniques
d'interiors cap a entorns exteriors peatonals no és evident, a causa de la major dimensió de l'entorn, del dinamisme
de l'escena provocada pels peatons i per altres obstacles en moviment, de la resposta de certs sensors a la
il.luminació natural, i de la constant presència d'elements tridimensionals tals com rampes, escales, voreres o forats.
D'altra banda, la localització de robots mòbils basada en GPS ha demostrat uns resultats insuficients de cara a una
navegació robusta i de llarga durada en entorns urbans.
Una de les peces clau en la navegació autònoma és la localització. En el cas que la localització consideri un mapa
conegut a priori, encara que no sigui un model complet de l'entorn, parlem d'una localització basada en un mapa.
Aquesta assumpció és realista ja que la tendència actual de les administracions locals és de construir mapes precisos
de les ciutats, especialment dels llocs d'interés tals com les zones més cèntriques. El fet de tenir els robots localitzats
en un mapa permet una planificació i una monitorització d'alt nivell, i així els robots poden arribar a destinacions
indicades sobre el mapa, tot seguint de forma deliberativa una ruta prèviament planificada.
Aquesta tesi tracta el tema de la localització de robots mòbils, basada en un mapa i per entorns urbans peatonals. La
proposta de la tesi utilitza el filtre de partícules, un mètode probabilístic i recursiu, ben conegut i àmpliament utilitzat
per la fusió de dades i l'estimació d'estats. Les principals contribucions de la tesi queden dividides en quatre aspectes:
(1) experimentació de llarga durada del seguiment de la posició, tant en 2D com en 3D, d'un robot mòbil en entorns
urbans reals, en el context de la navegació autònoma, (2) desenvolupament d'una tècnica ràpida i precisa per calcular
en temps d'execució els models d'observació de distàncies en entorns 3D, un requisit bàsic pel rendiment del filtre de
partícules a temps real, (3) formulació d'un filtre de partícules que integra conjunts de dades asíncrones i (4) proposta
teòrica per solucionar la localització global d'una manera activa i cooperativa, entenent la cooperació com el fet de
compartir informació, o bé com el de planificar accions conjuntes per solucionar un objectiu comú
Understanding scaling through history-dependent processes with collapsing sample space
History-dependent processes are ubiquitous in natural and social systems.
Many such stochastic processes, especially those that are associated with
complex systems, become more constrained as they unfold, meaning that their
sample-space, or their set of possible outcomes, reduces as they age. We
demonstrate that these sample-space reducing (SSR) processes necessarily lead
to Zipf's law in the rank distributions of their outcomes. We show that by
adding noise to SSR processes the corresponding rank distributions remain exact
power-laws, , where the exponent directly corresponds to
the mixing ratio of the SSR process and noise. This allows us to give a precise
meaning to the scaling exponent in terms of the degree to how much a given
process reduces its sample-space as it unfolds. Noisy SSR processes further
allow us to explain a wide range of scaling exponents in frequency
distributions ranging from to . We discuss several
applications showing how SSR processes can be used to understand Zipf's law in
word frequencies, and how they are related to diffusion processes in directed
networks, or ageing processes such as in fragmentation processes. SSR processes
provide a new alternative to understand the origin of scaling in complex
systems without the recourse to multiplicative, preferential, or self-organised
critical processes.Comment: 7 pages, 5 figures in Proceedings of the National Academy of Sciences
USA (published ahead of print April 13, 2015
Extreme robustness of scaling in sample space reducing processes explains Zipf's law in diffusion on directed networks
It has been shown recently that a specific class of path-dependent stochastic
processes, which reduce their sample space as they unfold, lead to exact
scaling laws in frequency and rank distributions. Such Sample Space Reducing
processes (SSRP) offer an alternative new mechanism to understand the emergence
of scaling in countless processes. The corresponding power law exponents were
shown to be related to noise levels in the process. Here we show that the
emergence of scaling is not limited to the simplest SSRPs, but holds for a huge
domain of stochastic processes that are characterized by non-uniform prior
distributions. We demonstrate mathematically that in the absence of noise the
scaling exponents converge to (Zipf's law) for almost all prior
distributions. As a consequence it becomes possible to fully understand
targeted diffusion on weighted directed networks and its associated scaling
laws law in node visit distributions. The presence of cycles can be properly
interpreted as playing the same role as noise in SSRPs and, accordingly,
determine the scaling exponents. The result that Zipf's law emerges as a
generic feature of diffusion on networks, regardless of its details, and that
the exponent of visiting times is related to the amount of cycles in a network
could be relevant for a series of applications in traffic-, transport- and
supply chain management.Comment: 11 pages, 5 figure
Sample space reducing cascading processes produce the full spectrum of scaling exponents
Sample Space Reducing (SSR) processes are simple stochastic processes that
offer a new route to understand scaling in path-dependent processes. Here we
define a cascading process that generalises the recently defined SSR processes
and is able to produce power laws with arbitrary exponents. We demonstrate
analytically that the frequency distributions of states are power laws with
exponents that coincide with the multiplication parameter of the cascading
process. In addition, we show that imposing energy conservation in SSR cascades
allows us to recover Fermi's classic result on the energy spectrum of cosmic
rays, with the universal exponent -2, which is independent of the
multiplication parameter of the cascade. Applications of the proposed process
include fragmentation processes or directed cascading diffusion on networks,
such as rumour or epidemic spreading.Comment: 10 pages, 6 figure
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