1,401 research outputs found
Automata-based Adaptive Behavior for Economical Modelling Using Game Theory
In this chapter, we deal with some specific domains of applications to game
theory. This is one of the major class of models in the new approaches of
modelling in the economic domain. For that, we use genetic automata which allow
to build adaptive strategies for the players. We explain how the automata-based
formalism proposed - matrix representation of automata with multiplicities -
allows to define semi-distance between the strategy behaviors. With that tools,
we are able to generate an automatic processus to compute emergent systems of
entities whose behaviors are represented by these genetic automata
Overview on agent-based social modelling and the use of formal languages
Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft
Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability
The integrated - environmental, economic and social - analysis of climate change calls for a paradigm shift as it is fundamentally a problem of complex, bottom-up and multi-agent human behaviour. There is a growing awareness that global environmental change dynamics and the related socio-economic implications involve a degree of complexity that requires an innovative modelling of combined social and ecological systems. Climate change policy can no longer be addressed separately from a broader context of adaptation and sustainability strategies. A vast body of literature on agent-based modelling (ABM) shows its potential to couple social and environmental models, to incorporate the influence of micro-level decision making in the system dynamics and to study the emergence of collective responses to policies. However, there are few publications which concretely apply this methodology to the study of climate change related issues. The analysis of the state of the art reported in this paper supports the idea that today ABM is an appropriate methodology for the bottom-up exploration of climate policies, especially because it can take into account adaptive behaviour and heterogeneity of the system's components.Review, Agent-Based Modelling, Socio-Ecosystems, Climate Change, Adaptation, Complexity.
Modeling Spatial Organization with Swarm Intelligence Processes
International audienceUrban Dynamics modeling needs to implement spatial organization emergence in order to describe the development of services evolution and their usage within spatial centers. In this paper, we propose an extension of the nest building algorithm with multi-center, multi-criteria and adaptive processes. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. Typically, this model is suitable to analyse and simulate urban dynamics like the evolution of cultural equipment in urban area
Refounding of Activity Concept ? Towards a Federative Paradigm for Modeling and Simulation
Journal : Simulation, Transactions of the Society for Modeling and Simulation InternationalInternational audienceCurrently, the widely used notion of activity is increasingly present in computer science. However, because this notion is used in specific contexts, it becomes vague. Here, the notion of activity is scrutinized in various contexts and, accord-ingly, put in perspective. It is discussed through four scientific disciplines: computer science, biology, economics, and epis-temology. The definition of activity usually used in simulation is extended to new qualitative and quantitative definitions. In computer science, biology and economics disciplines, the new simulation activity definition is first applied critically. Then, activity is discussed generally. In epistemology, activity is discussed, in a prospective way, as a possible framework in models of human beliefs and knowledge
Equation-Free Multiscale Computational Analysis of Individual-Based Epidemic Dynamics on Networks
The surveillance, analysis and ultimately the efficient long-term prediction
and control of epidemic dynamics appear to be one of the major challenges
nowadays. Detailed atomistic mathematical models play an important role towards
this aim. In this work it is shown how one can exploit the Equation Free
approach and optimization methods such as Simulated Annealing to bridge
detailed individual-based epidemic simulation with coarse-grained,
systems-level, analysis. The methodology provides a systematic approach for
analyzing the parametric behavior of complex/ multi-scale epidemic simulators
much more efficiently than simply simulating forward in time. It is shown how
steady state and (if required) time-dependent computations, stability
computations, as well as continuation and numerical bifurcation analysis can be
performed in a straightforward manner. The approach is illustrated through a
simple individual-based epidemic model deploying on a random regular connected
graph. Using the individual-based microscopic simulator as a black box
coarse-grained timestepper and with the aid of Simulated Annealing I compute
the coarse-grained equilibrium bifurcation diagram and analyze the stability of
the stationary states sidestepping the necessity of obtaining explicit closures
at the macroscopic level under a pairwise representation perspective
Fostering cooperation through dynamic coalition formation and partner switching
In this article we tackle the problem of maximizing cooperation among self-interested agents in a resource exchange environment. Our main concern is the design of mechanisms for maximizing cooperation among self-interested agents in a way that their profits increase by exchanging or trading with resources. Although dynamic coalition formation and partner switching (rewiring) have been shown to promote the emergence and maintenance of cooperation for self-interested agents, no prior work in the literature has investigated whether merging both mechanisms exhibits positive synergies that lead to increase cooperation even further. Therefore, we introduce and analyze a novel dynamic coalition formation mechanism, that uses partner switching, to help self-interested agents to increase their profits in a resource exchange environment. Our experiments show the effectiveness of our mechanism at increasing the agents' profits, as well as the emergence of trading as the preferred behavior over different types of complex networks. © 2014 ACM.The first author thanks the grant Formación de Profesorado Universitario (FPU), reference AP2010-1742. J.Ll.A. and J.A.R-A are partially funded by projects EVE (TIN2009-14702-C02-01), AT (CSD2007-0022), COR (TIN2012-38876-C02-01), MECER (201250E053), and the Generalitat of Catalunya grant 2009-SGR-1434Peer Reviewe
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