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Visual agent-based model development with repast simphony.
Abstract and Figures
Repast is a widely used, free, and open-source agent-based modeling and simulation toolkit. Three Repast platforms are currently available, each of which has the same core features but a different environment for these features. Repast Simphony (Repast S) extends the Repast portfolio by offering a new approach to simulation development and execution. This paper presents a model of physical infrastructure network interdependency as an introductory tutorial and illustration of the visual modeling capabilities of Repast S.
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... Even though MATSim offers a powerful traffic simulation platform, the main drawback (for our use-case) comes from the global approach adopted, since it is constructed to perform simulations in large-scale scenarios like big cities or even countries. The RePast Simphony [19] platform ( Figure 2-2) is a free and open-source agent-based modeling toolkit, which provides a library of classes for creating, running, displaying, and collecting data from an agent-based simulation. Its core and programming interface is based on Java programing language, which makes it less intuitive and syntactically heavy. ...
... 19. Traffic jam responsible for the prediction failure. ...
Today all major metropolises in France, Europe and the rest of the world suffer from severe problems of congestion and saturation of infrastructures, which concern both individual and public transport. Current transportation systems are reaching capacity limits and appear unable to absorb increases in passenger flows in the future. The transport of the future is part of the various so-called Smart City initiatives and should be ”intelligent”, that is to say not only react to the demands but anticipate them, relying on the data exchanged between the end user and the information system of transportation operators.Within this context, one of the main challenges is the creation of appropriate methodologies for analysis of geo-localized transport data for instantaneous storage, analysis, management and dissemination of massive (typically thousands of instant geo-localizations , with a refresh rate of the order of a few seconds) data flows. The related algorithms must be capable of managing event lists of several tens of minutes to calculate real trajectories, instantaneous occupations, traffic lights changing cycles as well as vehicular traffic flow forecasts.In this thesis, we address two different issues related to this topic.A first contribution concerns the optimization of the traffic lights systems. The objective is to minimize the total journey time of the vehicles that are present in a certain part of a city. To this purpose, we propose a PSO (Particle Swarm Optimization) technique. The experimental results obtained show that such an approach makes it possible to obtain significant gains (5.37% - 21.53%) in terms of global average journey time.The second part of the thesis is dedicated to the issue of traffic flow prediction. In particular, we focus on prediction of the bus arrival time in the various bus stations existent over a given itinerary. Here, our contributions first concern the introduction of a novel data model, so-called TDM (Traffic Density Matrix), which captures dynamically the situation of the traffic along a given bus itinerary. Then, we show how different machine learning (ML) techniques can exploit such a structure in order to perform efficient prediction. To this purpose, we consider first traditional ML techniques, including linear regression and support vector regression with various kernels. The analysis of the results show that increasing the level of non-linearity can lead to superior results. Based on this observation, we propose various deep learning techniques with hand-crafted networks that we have specifically adapted to our objectives. The proposed approach include recurrent neural networks, LSTM (Long Short Time Memory) approaches, fully connected and convolutional networks. The analysis of the obtained experimental results confirm our intuition and demonstrate that such highly non-linear techniques outperform the traditional approaches and are able to deal with the singularities of the data that in this case correspond to localized traffic jams that globally affect the behavior of the system.Due to the lack of availability of such highly sensitive type of geo-localized information, all the data considered in our experiments has been produced with the help of the SUMO (Simulation of Urban Mobility) microscopic simulator. We notably show how SUMO can be exploited to construct realistic scenarios, close to real-life situations and exploitable for analysis purposes.Interpretation and understanding the data is of vital importance, nevertheless an adequate visualization platform is needed to present the results in a visually pleasing and understandable manner. To this purpose, we finally propose two different visualization application, a first one dedicated to the operators and the second one to clients. To ensure the deployment and compatibility of such applications on different devices (desktop PCs, Laptops, Smartphones, tablets…) a scalable solution is proposed.
... A system allowing the emergence of a solution for any given matching scenario. Figure 5, our Reflex-SMAS prototype core was implemented in Java using the open source ABMS framework Repast Simphony (2.1) [19], and the open source framework for Text Similarity DKPro Similarity (2.1.0) [20]. ...
Several approaches are proposed to deal with the problem of the Automatic Schema Matching (ASM). The challenges and difficulties caused by the complexity and uncertainty characterizing both the process and the outcome of Schema Matching motivated us to investigate how bio-inspired emerging paradigm can help with understanding, managing, and ultimately overcoming those challenges. In this paper, we explain how we approached Automatic Schema Matching as a systemic and Complex Adaptive System (CAS) and how we modeled it using the approach of Agent-Based Modeling and Simulation (ABMS). This effort gives birth to a tool (prototype) for schema matching called Reflex-SMAS. A set of experiments demonstrates the viability of our approach on two main aspects: (i) effectiveness (increasing the quality of the found matchings) and (ii) efficiency (reducing the effort required for this efficiency). Our approach represents a significant paradigm-shift, in the field of Automatic Schema Matching.
... Using this agent propagation from each data point, NetLogo composes a Voronoi diagram of bisector lines between any pair of data points, on which agents propagated from a different point collide with each other. Repast Simphony [28] populates agents on all the four boundary lines of a 2D space and march them toward the center of the space. This is a simulation of wrapping data points with an elastic band, which forms the convex hull [29]. ...
While some spatial analytics in GIS are well-supported by combinations of data-streaming tools and machine-learning algorithms, (e.g., Spark and KNN on a geographic map), the others are tightly coupled with computational geometry. They handle multi-dimensional or graph structures that should be better maintained in distributed memory for the purpose of dynamic spatial analysis and repetitive geometric queries. We expect that dispatching agents as active data analyzers into datasets would work smoother than disassembling and conveying datasets into passive data-streaming tools. This research compared agent-based and data-streaming big-data parallelization in computational geometry. We parallelized the closest pair of points, the convex hull, the Euclidean shortest path, the point location, and the range search problems, using our MASS (multi-agent spatial simulation) library, MapReduce, and Spark. MASS performed best in three of the programs, which demonstrated agents’ strength in spatial analysis over many data points and repetitive geometric queries with deep tree traverses.
... All simulators in ecology deal with some kind of ecosystem representation, and thus should share a common conceptual background. But most often, their design is method-based rather than concept-based, leading to incompatible modelling worlds: differential equation systems (Gurney & Nisbet, 1998), cellular automata (Ermentrout & Edelstein-Keshet, 1993;Favier & Dubois, 2004;Hernandez Encinas et al., 2007;Muci et al., 2012), individual-based models (Grimm & Railsback, 2005) and multi-agent systems (Amouroux et al., 2009;Bellifemine et al., 2001;Minar et al., 1996;North et al., 2007;Wilensky, 1999). We argued (Gignoux et al., 2011) that the ecosystem concept, as proposed by Tansley (1935), was well adapted to simulation modelling: the ecosystem is a multi-aspect, scale-independent, observer-selected and recursive object. ...
Ecology, like many disciplines, commonly relies on simulation to provide insights into the dynamics of complex systems. Yet there are two unresolved problems for ecological studies relying on simulation. First, it is often the case that simulators representing the same system, designed for ostensibly the same purpose, differ in their results with the reasons buried deep within computer code. Second, ecology is a diverse discipline and each sub-discipline necessarily has its particular simulation methods. This raises a problem as to how models from these various fields can be coupled for transdisciplinary studies. We built a new simulation platform named 3Worlds, grounded on a concept familiar and common to all fields of ecology: the ecosystem. We defined the ecosystem for the purpose of simulation by a precise set of rules. The platform can implement models from fields as diverse as food web, population and landscape ecology, energy and material stocks and fluxes, and techniques such as agent-based, cellular automata and discrete-event simulation. In addition, we developed a dynamic graph to represent ecosystems as a set of interacting components. Our approach goes some way to unifying ecology for the purpose of simulation and reduces the problem of code comparison to a comparison of two graphs: (1) a specification graph that complies with the rules of what constitutes an ecosystem, and (2) the successive graph states of a particular simulation trajectory representing the ecosystem. Two applications constitute the core of 3Worlds. ModelMaker builds the ecosystem compliant model and ModelRunner executes the model represented as a dynamic graph. A library of ∼24 models illustrates how 3Worlds can simulate very different systems, from simple 1-equation 1-variable models to individual-based systems with thousands of ecosystem components.
... DLD was created using the Repast Simphony platform (North et al., 2013(North et al., , 2007(North et al., , 2005 and Java programming language (Arnold et al., 2005). We chose Repast Simphony due to its user friendly graphical user interface, its ability to incorporate raster files and shape files, the versatility of the Java programming language, and the ability to run from standalone batch files. ...
We developed a spatially explicit agent-based model (ABM), DeerLandscapeDisease (DLD), to investigate the effects of landscape structure, disease transmission, and management alternatives on dynamics of chronic wasting disease (CWD) in white-tailed deer (Odocoileus virginianus). We fitted biased random walk models to data from GPS-collared deer to simulate movements of individual deer and deer groups in an agricultural landscape with fragmented forest patches and a forest-dominated landscape. We estimated behavioral and demographic parameters from field data and published literature of deer ecology. We considered both direct and indirect transmission routes and assumed that bioavailability of infectious pathogens deposited in the environment decreased exponentially over time. We tuned transmission parameters to match observed trajectories of CWD prevalence in Wisconsin, and assumed that infection probability during an encounter was equal for all age classes. Thus, infection prevalence varied with sex- and age-specific behavior.
DLD simulations demonstrated significant effects of landscape structure, social behavior and transmission mode on temporal changes in prevalence. Prevalence rose faster and reached higher levels in fragmented forest landscapes due to aggregation of deer within small forest patches. Furthermore, simulation results suggested that CWD might be driven through a mix of frequency- and density-dependent processes, potentially facilitating coexistence of CWD and deer populations. These results demonstrate the utility of ABMs and the importance of including spatial and behavioral heterogeneity when modeling disease transmission.
... • What is the goal of the course: shall the students learn basic concepts of modelling and simulation (Schriber et al. 2013), about one modelling technique in more depth, e.g., DEVS (Van Tendeloo and Vangheluwe 2017), to apply a specific tool (North et al. 2007), about one type of task in simulation studies, e.g., experiment design, or shall oversee the conduction of entire simulation studies (Loper et al. 2019), or grasp broader scientific concepts, e.g., system thinking (Hung 2008)? • What is the format of the lectures? ...
... One of the most famous multi-agent system frameworks is the blackboard based system (BBS) whose history goes back to 1980's [1]. Open source frameworks such as GBBopen, 1 Repast [2] and Repast HPC [3] are used as the backbones of advanced science, engineering, and policy analysis. The BBS architecture provides a flexible framework to solve complex problems with blackboard, knowledge source (KS) and control shell. ...
A norm regulates the run-time behavior of the agent with the action and condition to trigger the action. Because of the incomplete understanding of the world, the
result
of the action may be different for the same agent with the ‘same’ context, or unintended different context. To study this phenomenon, the classical norm definition is extended from the condition-action pair to cover the
expectation
, in order to verify the result of the action. The Norm evolution can be defined as a gradual process which makes a norm more complete and effective. In the terminology of evolution, a norm is called
mutated
if the result contradicts to the expectation, i.e. at least one of the expected conditions is invalid. At run-time, norms are executed in series. A mutation brings new knowledge to the following states and might affect the later execution of the norms. Such knowledge provides will help the norm designer to complete the definitions. A mutation based norm evolution (Mone) method is proposed in this paper to detect the mutations, to propagate the evidence and to crossover the norms for completeness. The method is formalized in the Description Logic, and implemented with the algorithms for mutation detection and norm crossover. The case study illustrates the Description Logic
of the method and shows the potential to evolve the norms autonomously in the Blackboard system, GBBopen.
... In this article, the analysis is only limited to the most notable languages excluding the agent platforms and frameworks like Jade (Bellifemine et al., 2007), Janus (Gaud et al., 2009), Repast Simphony (North et al., 2007), NetLogo (Wilensky, 1999), and MARS (Hüning et al., 2016;Parker and Epstein, 2011) since they do not provide first-class abstractions at the language level, but rather extend an existing OOP language, which is usually Java. ...
SARL is a general-purpose agent-oriented programming language. This language aims at providing the fundamental abstractions for dealing with concurrency, distribution, interaction, decentralization, reactivity, autonomy and dynamic reconfiguration that are usually considered essential for implementing agent-based applications. Every programming language specifies an execution model. In the case of SARL, this execution model is defined based on the object- oriented paradigm, i.e. the run-time environment is written in Java. Accordingly, and by default, the SARL programs are transformed into their equivalent object- oriented programs written in Java. The goal of this paper is twofold. Firstly, to explain the mapping between the agent-oriented paradigm and the object-oriented paradigm. Secondly, to define transformations from the SARL constructs to the Java constructs. We advocate that these goals enable the SARL developers to understand the SARL statements, and the mapping to the equivalent executable entities.
This article describes Simexplorer, a computer framework for managing simulation experiments and, to some extent, the scientific quality of the modelling process. An information system, included in the framework, insures the traceability of the experiments and their reproducibility and thus contributes to the modelling process quality management. Moreover, this information system provides facilities for sharing and exchanging components of experiment scenarios. The authors illustrate the use of the framework on a simple example of modelling process.
This paper presents an introductory tutorial and illustration of the modeling capabilities of the Repast Simphony simulation framework using an agent-based model of regional natural gas and electric power system interdependencies. The natural gas transmission and distribution and electrical power companies are modeled as social agent organizations. The goal of the modeling exercise is to simulate impacts on the delivery of natural gas to the affected geographical regions and the effects of various policy models in the agent-based company models. Additionally, the estimate of cascading effects of natural gas loss on associated electric power infrastructure is investigated.
The physical layers in the simulation consists of a natural gas transmission network and DC electric transmission network.
The natural gas transmission model consists of a network of interconnected links and nodes, where the nodes function as delivery, receipt and/or pipeline termination points and the links function as gas pipelines that transport natural gas between nodes. Supplies, demands and compressor fuel usage values and compressor and pressure regulator characteristics may be modified to observe the effects on the network.
The DC electric network model considers a balance of demand and generation given the transmission topology. The nodes in the electric network represent generators and load points, while the links function as electrical transmission lines. The electric network model permits sensitivity analysis of line outages and shifts in generation. The two networks are connected via links between the natural gas network and gas-fired electric power plants (generators) in the electrical network. Each network is fairly large scale and contain several thousand nodes and links each.
The social agent layers consists of both regional and local gas transmission companies as well as local electrical power companies.
The regional natural gas transmission companies control the portion of the network between the gas supply and production sources. The local gas distribution company is responsible for delivery of the gas between the local city gates and the customer base (commercial and residential) Both natural gas companies share a common internal structure consisting of several groups such as operations, engineering and supply control. Each company group is modeled as a collection of different agent types, each with a unique type of behavior suited to their respective tasks. Certain agents act as a liaison between the companies and between the transmission and local distribution companies.
The social and physical agent models were developed in Repast [ROAD 2005], a widely used, free, and open source, agent-based modeling and simulation toolkit with three released platforms, namely Repast for Java, Repast for the Microsoft .NET framework, and Repast for Python Scripting (North et al 2005). Repast Simphony (Repast S) extends the Repast portfolio by offering a new approach to simulation development and execution (North et al 2006). Simphony goes beyond current model integration architectures that simultaneously require users with broad and deep knowledge in the application area, modeling, and software engineering. This broad skill set rarely exists within a single organization and is even less likely to be integrated into a working team. Simphony brings model integration tools directly to domain expert analysts (e.g., infrastructure specialists) without the need of software engineers, allowing users to develop integrated simulation modeling applications much more efficiently and economically than has been previously possible.
Simphony provides drag-and-drop user interfaces for: selecting from a repository of model components and tools (e.g., geographical information systems (GIS), visualization tools, statistical tools, and databases); creating new models using flow diagrams and agent-based model templates; assigning data sources such as GIS data, relational databases or real-time data feeds such as sensors; defining how components should interact; and controlling how the simulation is executed. The Simphony team is also investigating the use of grid computing technologies to provide large-scale simulation capabilities and distributed collaborative development of integrated national security applications.
To insure that Simphony directly addresses analyst’s needs, its design is based on a “Use Case” approach where example applications are presented to end users and progressively refined using their suggestions. Several use cases are being developed including infrastructure interdependency; natural gas disruption fast turn around analysis; energy process and market analysis; supply network infrastructures; and manufacturing and industrial processes.
Repast is a widely used, free, and open-source, agent-based modeling and simulation toolkit. Three Repast platforms are currently available, each of which has the same core features but a different environment for these features. Repast Simphony (Repast S) extends the Repast portfolio by offering a new approach to simulation development and execution. This paper presents a model of wolf-sheep predation as an introductory tutorial and illustration of the modeling capabilities of Repast S. We use a model of wolf-sheep predation to demonstrate the capabilities of the Repast S toolkit and as an introductory tutorial. While the example is not intended to model real phenomenon, the model's complexity is high enough to illustrate how the user may develop multi-agent models. Spatial and temporal patterns emerge in the model consisting of potentially hundreds of instances of three agent types. It is important to note that Repast S and its related tools are still under development. This paper presents the most current information at the time it was written. However, changes may occur before the planned final release.
ABSTRACT Repast is a ,widely used free and open-source agent-based modeling ,and simulation toolkit. Three Repast platforms are currently available, each of which has the same core features but a different ,environment ,for these features. Repast Simphony ,(Repast S) extends the Repast portfolio by offering,a new,approach to simulation,development,and execution. The Repast S development ,environment ,is expected ,to include ,advanced features for agent behavioral specification and dynamic,model self-assembly. This paper introduces the architecture and core features of the Repast S development environment. A related paper in the Agent 2005conference,proceedings by the same authors that is titled “Repast Simphony ,Runtime ,System” discusses ,the Repast S model ,execution environment. Keywords: Agent-based modeling and simulation, Repast, toolkits, development environments
ABSTRACT Repast is a ,widely used free and open-source agent-based modeling ,and simulation toolkit. Three Repast platforms are currently available, namely, Repast for Java (Repast J), Repast for the Microsoft .NET framework (Repast .NET), and Repast for Python Scripting (Repast Py). Each of these ,platforms has the same ,core features. However, each platform provides a different environment for these features. Taken together, the Repast platform portfolio gives modelers a choice of model development and execution environments. Repast Simphony ,(Repast S) extends the Repast portfolio byoffering,a new ,approach ,to simulation ,development ,and execution. The Repast S runtime is designed to include advanced features for agent storage, display, and behavioral activation, as well as new facilities for data analysis and presentation. This paper introduces the architecture and core features of the ,Repast S runtime ,system and discusses how ,Repast S fits within the larger Repast portfolio. A related paper in this Agent 2005 conference proceedings by the same authors, “Repast Simphony Development Environment,” discusses the Repast S model authoring system. Keywords: Agent-based modeling and simulation, Repast, toolkits, model execution, runtime system
Agent-based models have historically maintained a tight coupling between individuals, their behaviors, and the space in which they interact. As a result, many models have been designed in a way that limits their ability to express behaviors and interactions. In this paper, we propose a new approach toward designing simulations that builds upon the experiences of developing and working with several agent-based toolkits. This approach encourages flexibility and reusability of components and models. A preliminary implementation is the core structure of the upcoming Repast Simphony agent-based modeling and simulation toolkit. By creating a 'proto-space' called a Context, we provide model designers with a container that can maintain a localized state for agents. A Context's state can maintain multiple interaction spaces called Projections, as well as more typical state information. Projections are designed such that they can be used to represent a wide range of abstract spaces, from graphs to grids to realistic geographic spaces. Importantly, projections and agents or individuals are independent of one another. Agents can be agnostic toward the type of projection in which they are interacting, and projections can be agnostic toward the type of agents whose relationships they maintain. Finally, the context provides a logical location to maintain agent behaviors that are dependent on localized agent interactions and environment.
This paper discusses the integration of the dynamic object-oriented programming language Groovy into the Repast Simphony platform. It shows how the integration of Groovy benefits agent-based modeling in a number of ways, including its ability to simplify agent behavior specifications, create expressive and human-readable code, generate complex and adaptive agent behavior, and move between agent-modeling environments.
Many agent-based modeling and simulation researchers and practitioners have called for varying levels of simulation interoperability ranging from shared software architectures to common agent communications languages. These calls have been at least partially answered by several speci- fications and technologies. In fact, Tanenbaum (1988) has remarked that the "nice thing about standards is that there are so many to choose from." Tanenbaum goes on to say that "if you do not like any of them, you can just wait for next year's model." This article does not seek to introduce next year's model. Rather, the goal is to contribute to the larger simulation community the authors' accumulated experiences from developing several implementations of an agent-based simulation toolkit. As such, this article focuses on the implementation of simulation architectures rather than agent communications languages. It is hoped that ongoing architecture standards efforts will bene- fit from this new knowledge and use it to produce architecture standards with increased robustness.
Building Models in Repast Simphony: A Predator-Prey Example
- E Tatara
- M J North
- T R Howe
- N T Collier
- M T Parker
Tatara, E., M.J. North, T.R. Howe, N.T. Collier, and M.T. Parker, 2007a, "Building Models in
Repast Simphony: A Predator-Prey Example," Proceedings of the North American
Association for Computational Social and Organizational Sciences 2007 Conference, June
7-9, 2007, Emory -Atlanta, Georgia.
Flow4J-Eclipse Home Page
- A Greif
Greif, A., 2006, Flow4J-Eclipse Home Page; available at http://flow4jeclipse.sourceforge.net/.