679 research outputs found
A Mathematical Model for the Behavior of Individuals in a Social Field
Related to an idea of Lewin, a mathematical model for behavioral changes
under the influence of a social field is developed. The social field reflects
public opinion, social norms and trends. It is not only given by external
factors (the environment) but also by the interactions of individuals. Two
important kinds of interaction processes are distinguished: Imitative and
avoidance processes. Variations of individual behavior are taken into account
by ``diffusion coefficients''.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
A stochastic behavioral model and a `microscopic' foundation of evolutionary game theory
A stochastic model for behavioral changes by imitative pair interactions of
individuals is developed. `Microscopic' assumptions on the specific form of the
imitative processes lead to a stochastic version of the game dynamical
equations. That means, the approximate mean value equations of these equations
are the game dynamical equations of evolutionary game theory.
The stochastic version of the game dynamical equations allows the derivation
of covariance equations. These should always be solved along with the ordinary
game dynamical equations. On the one hand, the average behavior is affected by
the covariances so that the game dynamical equations must be corrected for
increasing covariances. Otherwise they may become invalid in the course of
time. On the other hand, the covariances are a measure for the reliability of
game dynamical descriptions. An increase of the covariances beyond a critical
value indicates a phase transition, i.e. a sudden change in the properties of
the considered social system.
The applicability and use of the introduced equations are illustrated by
computational results for the social self-organization of behavioral
conventions.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
A Mathematical Model for the Behavior of Pedestrians
The movement of pedestrians is supposed to show certain regularities which
can be best described by an ``algorithm'' for the individual behavior and is
easily simulated on computers. This behavior is assumed to be determined by an
intended velocity, by several attractive and repulsive effects and by
fluctuations. The movement of pedestrians is dependent on decisions, which have
the purpose of optimizing their behavior and can be explicitly modelled. Some
interesting applications of the model to real situations are given, especially
to formation of groups, behavior in queues, avoidance of collisions and
selection processes between behavioral alternatives.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Traffic Data and Their Implications for Consistent Traffic Flow Modeling
The paper analyzes traffic data of the Dutch freeway A9 with respect to
certain aspects which are relevant for traffic flow modeling as well as the
calibration of model parameters and functions. Apart from the dynamic velocity
distribution, the density-dependence and the temporal evolution of various,
partly lane-specific quantities is investigated. The results are well
compatible with recent macroscopic traffic flow models which have been derived
from the dynamics of driver-vehicle units. These have also solved the
inconsistencies, which previous models have been criticized for.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
New Ways to Promote Sustainability and Social Well-Being in a Complex, Strongly Interdependent World: The FuturICT Approach
FuturICT is one of six proposals currently being considered for support
within the European Commission's Flagship Initiative (see Box 1). The vision of
the FuturICT project is to develop new science and new information and
communication systems that will promote social self-organization,
self-regulation, well-being, sustainability, and resilience. One of the main
aims of the approach is to increase individual opportunities for social,
economic and political participation, combined with the creation of collective
awareness of the impact that human actions have on our world. This requires us
to mine large datasets ("Big Data") and to develop new methods and tools: a
Planetary Nervous System (PNS) to answer "What is (the state of the world)..."
questions, a Living Earth Simulator (LES) to study "What ... if ..." scenarios,
and a Global Participatory Platform (GPP) for social exploration and
interaction.Comment: For related work see http://www.soms.ethz.ch and
http://www.futurict.e
Qualified Trust, not Surveillance, is the Basis of a Stable Society
Peaceful citizens and hard-working taxpayers are under government
surveillance. Confidential communication of journalists is intercepted.
Civilians are killed by drones, without a chance to prove their innocence. How
could it come that far? And what are the alternatives?Comment: For related work see http://www.futurict.e
Survival Analysis, Master Equation, Efficient Simulation of Path-Related Quantities, and Hidden State Concept of Transitions
This paper presents and derives the interrelations between survival analysis
and master equation. Survival analysis deals with modeling the transitions
between succeeding states of a system in terms of hazard rates. Questions
related with this are the timing and sequencing of the states of a time series.
The frequency and characteristics of time series can be investigated by
Monte-Carlo simulations. If one is interested in cross-sectional data connected
with the stochastic process under consideration, one needs to know the temporal
evolution of the distribution of states. This can be obtained by simulation of
the associated master equation. Some new formulas allow the determination of
path-related (i.e. longitudinal) quantities like the occurence probability, the
occurence time distribution, or the effective cumulative life-time distribution
of a certain sequencing of states (path). These can be efficiently evaluated
with a recently developed simulation tool (EPIS). The effective cumulative
life-time distribution facilitates the formulation of a hidden state concept of
behavioral changes which allows an interpretation of the respective
time-dependence of hazard rates. Hidden states represent states which are
either not phenomenological distinguishable from other states, not externally
measurable, or simply not detected.Comment: For related work see
http://www.theo2.physik.uni-stuttgart.de/helbing.htm
Production, Supply, and Traffic Systems: A Unified Description
The transport of products between different suppliers or production units can
be described similarly to driven many-particle and traffic systems. We
introduce equations for the flow of goods in supply networks and the adaptation
of production speeds. Moreover, we present two examples: The case of linear
(sequential) supply chains and the case of re-entrant production. In
particular, we discuss the stability conditions, dynamic solutions, and
resonance phenomena causing the frequently observed "bullwhip effect", which is
an analogue of stop-and-go traffic. Finally, we show how to treat discrete
units and cycle times, which can be applied to the description of vehicle
queues and travel times in freeway networks.Comment: For related work see http://www.helbing.or
Responding to complexity in socio-economic systems: How to build a smart and resilient society?
The world is changing at an ever-increasing pace. And it has changed in a
much more fundamental way than one would think, primarily because it has become
more connected and interdependent than in our entire history. Every new
product, every new invention can be combined with those that existed before,
thereby creating an explosion of complexity: structural complexity, dynamic
complexity, functional complexity, and algorithmic complexity. How to respond
to this challenge? And what are the costs?Comment: For related publications see http://www.coss.ethz.ch and
http://scholar.google.com/citations?user=ebrNfPAAAAAJ&hl=e
The FuturIcT Knowledge Accelerator: Unleashing the Power of Information for a Sustainable Future
With our knowledge of the universe, we have sent men to the moon. We know
microscopic details of objects around us and within us. And yet we know
relatively little about how our society works and how it reacts to changes
brought upon it. Humankind is now facing serious crises for which we must
develop new ways to tackle the global challenges of humanity in the 21st
century. With connectivity between people rapidly increasing, we are now able
to exploit information and communication technologies to achieve major
breakthroughs that go beyond the step-wise improvements in other areas.
The need of a socio-economic knowledge collider was first pointed out in the
OECD Global Science Forum on Applications of Complexity Science for Public
Policy in Erice from October 5 to 7, 2008. Since then, many scientists have
called for a large-scale ICT-based research initiative on
techno-socialeconomic- environmental issues, sometimes phrased as a Manhattan-,
Apollo-, or CERN-like project to study the way our living planet works in a
social dimension. Due to the connotations, we use the term knowledge
accelerator, here.Comment: For related information see http://www.futurict.eu (The spelling
error in Sec. 2.5 was removed: "exclusion" was replaced by "inclusion"
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