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Mobidyc, a Generic Multi-Agents Simulator for Modeling Populations Dynamics.
Abstract
We present a simulator designed to help scientists who are not experts in computing, such as biologists, to build up, run, and update their models in the field of fish population dynamics. This simulator, written in Smalltalk, is built upon multi-agents concepts and is well suited to model systems where individual or spatial aspects are involved. It provides tools to set the state and the behavior of the agents and to set their environment. The pre-defined components should preferably be used, but help for customizing components or programming new ones i s supplied, in order to build more complex agents. The simulator manages qualitative and quantitative variables with simple or composed units, dependencies on parameters, synchronous and asynchronous modes within and between agents, and the importation of ASCII files for the scenario scripts or for the initial stocking of the agents. Four examples of applications are presented.
... The goal is to help users which want to create models or/and applications. We can divide these researches into three levels: methodologies (TROPOS [7] or Adelfe [17]), languages (AUML [2], AML [8], Ploom [11] or SMAL [19]) and frameworks (MadKit [13], SWARM [15] or Mobidyc [12]). Each methodology, language and framework contains several specific characteristics. ...
Several methodologies based on Multi-agent Systems (MAS) already exist. They help designers to describe software or to create MAS which aim at solving complex problems by simulations. Due to used formalisms, a methodology may be more or less generic. In this context, we have created a mobility oriented methodology called RAFALESP based on multi-agent systems. It helps us to describe mobiles which move on a space. This environment can be a virtual representation of a real space like a town where unpredictable events arise. We apply our methodology to solve problems which come from different research areas. We use it to find answers to geographical problems. The presented methodology begins by a conceptual representation of each mobile type and finishes by a mobility simulator. It uses several formalisms: UML and Ploom-Unity. They allows us to define mobiles, their interactions and their environment. According to their knowledge, their behaviour rules, mobiles moves on a space by following few motion types. They get an individual perception of the world. In this paper we focus on mobile perception description.
... @BULLET specific frameworks (Mobidyc [8]) are straightforward. They can be used in a narrow panel of situations. ...
Mobility study is composed of many research areas like urban mobility. In the literature, urban mobilities are represented by analytical techniques like stochastic laws or they are defined by simulation tools like multi-agents systems (MAS). The goal of our work is to define citizen behaviour in order to observe population dynamics by a simulation. This strategy is facilitated by a meta-model and a toolkit which are used with a particular method. The latter begins by a conceptual representation of each mobile and finishes by a mobility simulator. This paper aims at describing the mobility simulation toolkit. Thanks to this framework, mobility simulator development is simplified. It allows us to create distributed applications which are based on MAS.
La modélisation et la simulation des systèmes complexes sont basées principalement sur leur décomposition en sous-systèmes plus simples à manipuler. Ce découpage doit se faire de façon méthodique par l‟identification et la définition complète des différentes structures, actions et interactions qui régissent ces sous-systèmes. Généralement, le comportement du modèle global peut se déduire de l‟émergence des comportements des modèles représentant ces sous-systèmes. Plusieurs travaux de recherche et de nombreuses implémentations ont été conduits sur le thème de la modélisation et de la simulation des systèmes complexes. De ce fait, il existe aujourd‟hui une grande panoplie de méthodes, d‟outils et de produits logiciels dans ce cadre. Le travail présenté dans cette thèse est une contribution dans le domaine de la modélisation et de la simulation des systèmes complexes ; particulièrement, les processus industriels complexes. Après avoir mené une étude approfondie dans le cadre de la modélisation et de la simulation des systèmes complexes, l‟approche proposée se base principalement sur la transformation des modèles DEVS (Discrete EVent system Specification) en modèles agent afin qu‟ils soient simulables et implémentables au sein de plateformes multi-agents. En particulier, le modèle AGR (Agent/Groupe/Rôle) qui est un modèle conceptuel sous-jacent du modèle organisationnel AALAADIN, permet une décomposition d‟un système complexe en groupes d‟agents tout en déterminant toutes les interactions entre les groupes et les agents qui les composent ainsi que les rôles joués par les agents dans ces groupes. Dans l‟approche préconisée ; la décomposition du système global en sous-systèmes apparait à deux niveaux : Au niveau le plus bas ; la décomposition porte sur la division du processus global en modèles atomiques et couplés basés sur le formalisme DEVS. Ces modèles atomiques et couplés obtenus peuvent alors être formellement vérifiés et validés. A un niveau plus élevé, ces modèles sont mis en oeuvre et implémentés grâce aux Systèmes Multi-Agents (SMA). Ainsi, les modèles atomiques sont transformés en agents et les modèles couplés en groupes d‟agents. L‟environnement dans lequel évoluent les agents est représenté par l‟ensemble des données et informations partagé par les agents et qui leur sont accessibles par les transmissions de messages. Une version de ce travail a été implémentée sur la plate-forme multi-agents MAD-KIT et a abouti à l‟implémentation d‟un simulateur industriel.L‟avantage de cette démarche est son adaptabilité ainsi que les possibilités d‟extension. De plus la décomposition en sous-systèmes réduit considérablement la complexité des éléments mis en oeuvre et permet, ainsi une grande modularité et une meilleure lisibilité du système. Ce travail est réalisé en collaboration avec les départements de production et technique de liquéfaction du gaz naturel (GL1/k Skikda), un des principaux pôles d'hydrocarbures du complexe SONATRACH en Algérie.
Object-oriented programming has had a long-standing history with simulation systems in terms of human-computer interaction [1] dating back to Simula and early versions of Smalltalk-72 and Smalltalk-76. These frameworks were based on discrete, event-based simulations as revealed by the classic simulation examples of Smalltalk-80 Blue-book [2]. Nevertheless present time trends have pivoted towards agent-based modelling and abstractions, with systems like NetLogo capturing a sizeable following and heed. Two of the widely known agent-based modelling (ABM) platforms in Smalltalk (MobiDyC and CORMAS) have recently begun experimenting with porting their systems to Pharo. The rationale behind this choice is to allow modern re-imagination of the platforms that can take advantage of developments in: agile visualization, moldable tools, domain-specific languages (DSLs) and so on. This work focuses on the salient user interface component of these platforms, namely the spatial interface, which empowers a user to visualize the evolution of the system through time. We start with a concise analysis of the state-of-the-art for spatial interfaces and their platforms (MobiDyC, NetLogo, GAMA and CORMAS), scrutinizing in terms of programming flexibility, extensibility, portability, scalability, and interaction. Subsequently we highlight our on-going efforts in building an open-source extension for CORMAS' spatial interface in Pharo. In closing, we detail the pragmatic experience gained in the course of our work and present future perspectives.
Les travaux que j’ai menés sont engagés : ils ont pour but de renforcer les capacités des acteurs les moins favorisés des socio-écosystèmes à prendre part à des ateliers de concertation multi-acteurs. Ils reposent sur le postulat qu’une concertation effective demande un partage équilibré des différents points de vue des protagonistes. Pour partager des points de vue, il faut que chacun puisse exprimer le sien de manière intelligible pour les autres. En employant une démarche inductive fondée sur des expériences de co-conception dirigée par la simulation interactive de modèles multi-agent de type « empirique stylisé » réalisées avec des acteurs locaux dans des contextes et des domaines d’application très variés (France, Bhoutan, Thaïlande, Cameroun, Zimbabwe), j’ai progressivement dessiné les contours d’une mise en œuvre de la modélisation d’accompagnement qui repose sur les principes méthodologiques suivants :
i. constituer un groupe composé de 2-3 chercheurs pour élaborer une ébauche d’un modèle de simulation multi-agent proposant une représentation du système-cible stylisée, volontairement simpliste, et manipulable en mode interactif (les actions des agents sont décidées par les participants),
ii. convier un petit groupe d’acteurs locaux à un premier atelier pour « tester » cette version d’amorçage du processus et identifier tous les aspects nécessitant à leurs yeux d’être repris ou intégrés dans le modèle pour que celui-ci constitue une représentation du système-cible permettant de mettre en discussion une problématique formulée collectivement,
iii. engager le groupe de co-designers ainsi constitué dans une série d’ateliers de co-construction basés sur le test de la version à chaque fois actualisée du simulateur,
iv. utiliser la version finalisée du simulateur au cours d’ateliers co-animés par un groupe réduit de co-designers auxquels sont conviés d’autres types d’acteurs pour « tester » (selon les principes énoncés au point ii) cette version.
Je fais l’hypothèse que cette approche, en stimulant l’apprentissage social, favorise l’émergence de formes d’interactions coopératives entre les participants et ouvre ainsi la voie à l’action collective.
Résumé. Après avoir situé la contribution des approches multi-agents dans le domaine de la modélisation et de la simulation et cerné son domaine d'applicabilité, nous présentons brièvement ce qui a été réalisé dans le domaine de l'écologie et de la sociologie avant de présenter quelques plate-formes existantes. Nous concluons finalement par quelques perspectives de recherche.
This paper describes the fundamentals of a research project which is being launched in the emerging field of Ambient Intelligence as defined by the European Union’s 6th Research Program on Information Society. Massively multi-agent systems is the natural
technique for implementing Ambient Intelligence. Adaptivity is one of the key features of ambient systems. Ensuring that the
evolution of an ambient system is predictable and desirable is a challenging open design issue. We propose a user-driven approach
to adaptation. We call it “Adaptive Modeling” because it relies on the architectural style known as Adaptive Object-Models.
This provides us with a design method and tool for agents to be used in this context. Systems built with this method allow
non-programmer domain experts to locally modify the structure and behavior of agents at runtime, and thus obtain system-level
adaptation. Expert-driven adaptation should ensure the appropriateness of the system’s behavior with respect to its requirements.
We illustrate our method with an existing multi-agent system. Work is under way for extending it with other features, notably
fault-tolerance, as well as “agent-driven adaptation” by replacing expert users with monitoring agents endowed with the same
expertise.
KeywordsMassively Multiagent Systems-Adaptive Object-Models-Ambient Intelligence-Adaptive Agent
Nowadays, multiagent systems are very often used to run environmental simulations. These simulations need to use real environmental information. Unfortunately organizations (or companies), which can be everywhere in the world, very often hold these information. This fact has brought us to build a generic multiagent platform that is able to dynamically get distributed information throughout Internet. This platform can use two different network protocols: UDP and the RMI technology provided by Java. We explain in this paper how this platform is implemented and we give some benchmarks in order to compare the best solution for us between UDP and RMI. Finally, we applied this architecture to a case study: the shoal of swordfishes motion
This paper presents an interesting architecture to model the
environment in multiagent simulations. The originality of our approach
is that unlike the majority of multiagent systems, we do not perform
tasks dedicated to the environment and tasks dedicated together in the
same entity. This is why we separate an agent into two entities: the
brain that is in charge of reasoning, and the body that is in charge of
the perceptions and actions in the environment. We then propose a
mechanism which decreases the complexity of the environment. For that,
we define two new notions: environment porosity and aggregation
operation. We then applied this framework to the motion of a shoal of
swordfish
The influence of nest site selection on population dynamics is explored by considering two reproductive strategies. The first one, described as opportunist, is the most common in ecology. It postulates that an individual tries to select and track the optimal environmental conditions that maximize its total reproductive output. The second one, described as obstinate, comes from a generalization of "natal homing" recently proposed by Cury (1994). It assumes that a newborn individual memorizes early environmental cues that later determine its reproductive environment. We use an individual-based model named SEALAB to track artificial fish in a heterogeneous environment displayed as a lattice of hexagonal patches. The effects of two components of the lattice structure—namely the composition (amount of each patch type) and the configuration (spatial arrangement of patches)—on the success of the searching behavior are examined. For the obstinate strategy, whose searching behavior is characterized by a simple random walk, a spatial redundancy index seems sufficient to account for the spatial heterogeneity influence, whereas for the opportunist strategy, more subtle indices are needed. We develop a quantitative measure of spatial local optima that could apply to any searching behavior based on local hill-climbing or local gradient information. Our results indicate how heterogeneity causes opportunist individuals to get stuck in local spatial optima. The use of a spatially explicit individual-based model such as SEALAB is justified by the possibility of carefully estimating simultaneously the value and the sensitivity of global parameters in relation to the spatial heterogeneity of the environment.
Individual-based simulation modeling tracks the attributes of individual fish through time and aggregates them to generate insights into population function. By seeking to understand how fish of differing phenotypes respond to variations in physicochemical and biological environments, analysts hope to improve predictions of population trends. A review of eight accompanying papers highlights the promise and current limitations of the individual-based approach. Among the challenges to be faced are accurately representing feeding encounter rates, extending models to account for spatial heterogeneity and transgenerational responses, dealing with practical limits to the amount of data on individuals that can be measured and managed, more fully conceptionalizing natural processes, and acquiring appropriate field data with which to formulate and test the models. 16 refs., 1 tab.
This paper describes the Hobo simulation system that provides object-oriented library tools for development of individual-oriented ecological models: basic building blocks for various spatial configurations, general structure for defining a diverse community of model entities capable of a rich behaviour, output-related tools and user interface. It is argued that individual-oriented modelling is applicable to populations with very high abundances since the local view of an individual can be retained even for aggregated entities. For this purpose, a mechanism is designed allowing simulation of encounters of an individual with particles of a known concentration (e.g., prey). A simple simulation example is given on the effects of a spatial behaviour of grazers - herd formation - on their feeding outcome.
Fish populations consist of non-identical individuals inhabiting heterogeneous environments and moving about the environment in a manner that maximizes their individual fitness. No study has fully integrated these characteristics of fish populations into a single model. In this paper we propose a new class of model that includes each characteristic in a unified description of populations. To lay the foundation for these models we review models concerning (1) population dynamics in heterogeneous environments, (2) the effects of individual variability on population dynamics, and (3) individual movement and habitat selection rules. The models that we propose allow investigators to explore the population-level consequences of novel changes in the environment, and of different individual fitness maximization strategies. The strengths of our proposed class of model lie in their mechanistic, individual-level description of fish growth, movement and survival. Correctly depicting these mechanisms presents important challenges in developing such models. Despite these challenges, mechanistic models like those we propose should greatly increase our understanding of the interaction between environmental heterogeneity and fish population dynamics and distributions.
This paper presents an object-oriented approach to ecological modelling, and develops the underlying concepts into a structure which relates a set of “ecological” objects by means of a server, or shell, which effectively allows these to interact with each other, and displays the results of their interaction. An ecological model, ECOWIN, has been developed using this methodology, and this work examines the framework of the model, and describes its general layout. The basic structure of each object consists of a public section, which interacts with other objects and with the shell, and a private section, which carries out the activities which are characteristic of the object. The forms in which objects interact, and some of the advantages and difficulties of those interactions are discussed. Some “typical” objects are characterised, with the focus on the possibilities of adaptation and extensibility, using for instance, the concepts of inheritance and polymorphism. Some results obtained during the development and testing of the model in two different estuarine ecosystems are also shown, providing a practical application of the concepts and methodologies discussed herein. The virtues of using an object-oriented approach to ecological modeling appear to be, on the one hand, the ease of development and flexibility associated with the modularity and inheritance properties of the objects themselves, and on the other, the much greater conceptual approximation between natural ecosystems and interacting objects, relative to conventional structured programming methods.
The purpose of this study is to construct a model that can predict the impact on fisheries caused by coastal development activities. To accomplish this, many species of fish must be incorporated in the model, because each type of fish has a different value as a fishery resource and a different behavior for the same impact. In addition the effect of fish swimming must be considered because even when the total resource amount of fish does not change, fish may still disappear from the object area. These factors make the model structure complicated. Meanwhile, a new concept called ‘object oriented programming’ (OOP) is attracting the attention of modellers. In this paper, we have constructed a model called the ‘hallow-sea ecological model’ (SSEM), by using Smalltalk, which is representative of the OOP language. This showed that the fishing ground environment are expressed very flexibly and plainly by Smalltalk. Furthermore, we incorporated the effect of fish swimming by preference using a multicriteria analysis. The result of numerical experiments suggested that the effect of fish swimming by preference may be the essential factor for shallow-sea ecological modelling.
Until fairly recently, populations were handled as homogenized averages, which made modeling feasible but which ignored the essential fact that in any population there is a great variety of individuals of different ages, sizes, and degrees of fitness. Recently, because of the increased availability of affordable computer power, approaches have been developed which are able to recognize individual differences. Individual-based models are of great use in the areas of aquatic ecology, terrestrial ecology, landscape or physiological ecology, terrestrial ecology, landscape or physiological ecology, and agriculture. This book discusses which biological problems individual-based models can solve, as well as the models’ inherent limitations. It explores likely future directions of theoretical development in these models, as well as currently feasible management applications and the best mathematical approaches and computer languages to use. The book also details specific applications to theory and management.