A Graphical Development Method for Multiagent Simulators

Welcome to the Eighth Annual Workshop on Evolutionary Computation and Multi-Agent Systems and Simulation (ECoMASS 2014)! Evolutionary computation (EC) and multi-agent systems and simulation (MASS) both involve populations of agents. EC is a learning technique by which populations of individual agents adapt according to the selection pressures exerted by an environment; MASS seeks to understand how to coordinate the actions of a population of (possibly selfish) autonomous agents that share an environment so that some outcome is achieved. Both EC and MASS have top-down and bottom up features. For example, some aspects of multi-agent system engineering (e.g., mechanism design) are concerned with how top-down structure can constrain or influence individual decisions. Similarly, most work in EC is concerned with how to engineer selective pressures to drive the evolution of individual behavior towards some desired goal. Multi-agent simulation (also called agent-based modeling) addresses the bottom-up issue of how collective behavior emerges from individual action. Likewise, the study of evolutionary dynamics within EC (for example in coevolution) often considers how population-level phenomena emerge from individual-level interactions. Thus, at a high level, we may view EC and MASS as examining and utilizing analogous processes. It is therefore natural to consider how knowledge gained within EC may be relevant to MASS, and vice versa; indeed, applications and techniques from one field have often made use of technologies and algorithms from the other field. Studying EC and MASS in combination is warranted and has the potential to contribute to both fields. The ECoMASS Workshop at GECCO has a successful history as a forum for exploring precisely this intersection, and we are looking forward to another year of stimulating discussion, bringing together experts as well as novices in both areas, to engage in dialogue about their work. This year's participants bring a variety of topics for discussion, including migratory flows, the beating of the heart, embedded systems, pelotons and cyclists, and flocking behavior. This year, we will also be adding a research slam. We will be inviting presenters who are presenting in the general conference to give us a quick presentation about their work. We hope that this will further encourage additional lively discussion about a wide range of topics. We also encourage presenters to demonstrate their software live during a breakout session, enabling additional opportunities for one-on-one dialogue and discussion of actual running systems. Through these additions to the workshop, we hope to continue to innovate, and develop the conversations around the interesting intersection of evolutionary computation and multi-agent systems and simulations!

With the development and popularization of Internet, distance education has already entered the stage based on Web. Due to the shortcomings of traditional methods in developing Web application, the MVC (model-view-controller) pattern is introduced. The separation of logic programming from interface design is effectively archived by the three kinds of technology correlated with Java: JSP, Servlet and JavaBeans. This paper analyses MVC pattern. On the purpose of the unanimous solution of distance education and commercialization, an improved MVC pattern based on the conventional one is introduced. The practice of developing the distance education system proved the improved pattern is feasible.

Most economic and business systems are complex, dynamic, and nondeterministic systems. Different modeling techniques have been used for representing real life economic and business organizations either on a macro level (such as national economics) or micro level (such as business processes within a firm or strategies within an industry). Even though general computer simulation was used for modeling various systems (Zeigler, 1976) since the 1970s the limitation of computer resources did not allow for in-depth simulation of dynamic social phenomena. The dynamics of social systems and impact of the behavior of individual entities in social constructs were modeled using mathematical modeling or system dynamics. With the growing interest in multi agent systems that led to its standardization in the 1990s, multi agent systems were proposed for the use of modeling social systems (Gilbert & Conte, 1995). Multi agent simulation was able to provide a high level disintegration of the models and proper treatment of inhomogeneity and individualism of the agents, thus allowing for simulation of cooperation and competition. A number of simulation models were developed in the research of biological and ecological systems, such as models for testing the behavior and communication between social insects (bees and ants). Artificial systems for testing hypothesis about social order and norms, as well as ancient societies (Kohler, Gumerman, & Reynolds, 2005) were also simulated. Since then, agent-based modeling and simulation (ABMS) established itself as an attractive modeling technique (Klugl, 2001; Moss & Davidsson, 2001). Numerous software toolkits were released, such as Swarm, Repast, MASON and SeSAm. These toolkits make agent-based modeling easy enough to be attractive to practitioners from a variety of subject areas dealing with social interactions. They make agent-based modeling accessible to a large number of analysts with less programming experience.

In recent years, the introduction of electric vehicles (EVs) has become increasingly desirable from an environmental perspective. However, it is important to develop suitable charging equipment and infrastructure, as EVs tend to have shorter cruising distances than gasoline-powered vehicles. Various data-driven methods have been proposed for the placement of charging stations (CSs). To date, however, there have been few simulation-driven approaches that can take account of the microscale interactions among vehicles. Therefore, in this paper, we propose an efficient placement method based on multi-agent traffic simulations with an improved scoring function. In addition, as the number of CSs increase in proportion to the spread of EVs, we solve a multiple location design problem formulated as a combinatorial optimization technique. Numerical experiments were conducted on a realistic network in the central part of Wakayama Prefecture in Japan, and it was shown that the proposed method could improve the performance indicator of CS placement compared with the conventional method. Furthermore, the scenario of multiple CS installations at one time demonstrated that good combinations could be obtained.

The coordinated development of a complex system refers to the harmonious and coherent evolution of its subsystems. From the perspective of the coordinated development of ecological–economic–social complex systems, this paper analyzes the coordinated development mechanism (CDM) of the mariculture ecological–economic–social (MEES) complex system, constructs a coordinated development evaluation indicator system for the MEES complex system, and adopts the comprehensive evaluation model and the coupling coordination degree (CCD) model to empirically analyze the coordinated development level of the MEES complex system in China from 2009 to 2020. The results show that the comprehensive development level of China’s MEES complex system has improved significantly during this period, with the comprehensive development index increasing from 0.25 in 2009 to 0.76 in 2020, transitioning from a poor to an excellent status. Simultaneously, the CCD of the system increased progressively, experiencing phases of near dissonance, barely coupling coordination, primary coordination, and intermediate coordination, before finally reaching a stage of good coordination. Based on these findings, we further discuss and propose countermeasures to promote the coordinated development of China’s MEES complex system.

The hope of finding a new outlook on the world, new methods of cognition and prediction of course of historical processes, may be connected with the theory of self-organization of complex systems, called also synergetics, as a new interdisciplinary field of research. Synergetics facilitates our understanding of evolutionary pathways of the complex social and human systems, the causes of evolutionary crises, the threats of catastrophes, the reliability of forecasts and the principle limits of predictability in ecology, sociology, economy, geo-policy. Synergetics provides us with the knowledge of constructive principles of co-evolution of complex social systems, co-evolution of countries and geopolitical regions being at different stages of development, integration of the East and the West, the North and the South. Due to the growth of population on the Earth in blow-up regime, the general and local instability of development is increasing. The social world seems to go towards a unity, a sustainable commonwealth through a pulsation rather than monotonously. It goes via alternation of disintegration, even if partial, and getting more powerful integration of structures. There is a pathway of multiple reduction of temporal and material expenses, path of a resonant excitation of a desirable and - that is not less important - feasible in a given social system structure. In the case of right topology of integration of geopolitical structures, an arising whole organization can accelerate its tempo of evolution.

Model-View-Controller (MVC) pattern is very useful and popular design pattern that separates the modeling of the domain, the presentation, and the actions based on user input into three separate classes. The model acts as the domain that software is built around, the view as the visual representation of a model. It is usually the resulting markup that the framework renders to the browser and the controller responsible for processing input, acting upon the model, and deciding on what action should be performed, such as rendering a view or redirecting to another page for supporting a business models. Hadoop MapReduce paradigm applied for collected the several datasets for generating the large volume of data in batch processing. In this paper enhanced the Hadoop MapReduce for processing large scale and different data set across platform with MVC pattern. In general, the system consists of five mainly methods: 1.) Collected data sources from different platforms such as the registrar system, web mail, web blogs, news and the English Wikipedia that are included in the data file system at local system, 2.) Generate the data into a map slot from input format, 3.) calculate the jobs from the business logic, 4.) Create a data model based on data entity framework, and 5.) Display an user interface for supporting the business interfaces.

Multi-Agent Systems (MAS) can be used to model systems where the global behavior cannot be uniformly represented by standard techniques such as partial differential equations or linear systems because the system elements have their own independent behavior. This is, for instance, the case in complex systems such as daily mobility in a city for example. Depending on the system size the computing power needs for the MAS may be as big as for more traditional linear numerical systems and may need to be parallelized to fully represent real systems. Graphical Processing Units (GPU) have already proven to be an efficient support to execute large linear programs. In this paper we present the use of GPU for the execution of Sworm, a multi-scale MAS system. We show that GPU computing can be efficient in that less regular case and when the agent behavior is simple. We advocate for a wider use of the GPU in Agent Based Models in particular for multi-scale systems with work distribution between the CPU and GPU.

Cílem příspěvku je představit systémovou dynamiku, která pomáhá při řešení složitých problémů, a je pomůckou pro lepší pochopení okolních systémů. Systémová dynamika je zvláště užitečná pro analýzu systémů s vysokým stupněm detailní a dynamické komplexity, jako jsou komplexní sociální systémy. Ekonomický systém je typickým příkladem komplexního sociálního systému. Autor, s důrazem na povahu ekonomicko-sociálních systémů, ilustruje základní logiku systémové dynamiky a její vztah k aplikované informatice.

Epidemic spread poses a new challenge to the public health community. Given its very rapid spread, public health decision makers are mobilized to fight and stop it by setting disposal several tools. This ongoing research aims to design and develop a new system based on Multi-Agent System, Suscpetible-Infected-Removed (SIR) model and Geographic Information System (GIS) for public health officials. The proposed system aimed to find out the real and responsible factors for the epidemic spread and explaining its emergence in human population. Moreover, it allows to monitor the disease spread in space and time and provides rapid early warning alert of disease outbreaks. In this paper, a multi-agent epidemic spread simulation system is proposed, discussed and implemented. Simulation result shows that the proposed multi-agent disease spread system performs well in reflecting the evolution of dynamic disease spread system's behavior

Multi-Agent System (MAS) is a suitable programming paradigm for simulating and modeling health care systems and applications, where resources, data, control and services are widely distributed. We have developed a multi-agent software prototype to simulate the activities and roles inside a health care system. The prototype is developed using a framework called Role-based Agent Development Environment (RADE). In this chapter, the authors present an integrated approach for modeling, designing and implementing a multi-agent health care simulation system using RADE. They describe the definition of role classes and agent classes, as well as the automatic agent generation process. The authors illustrate the coordination problem and present a rule-based coordination approach. In the end, they present a runtime scenario of this health care simulation system, which demonstrates that dynamic task allocation can be achieved through the creation of role instances and the mapping from role instances to agents. This scenario also explains how agents coordinate their activities given their local constraints and interdependence among distributed tasks.

Forming comprehensive security plans is essential to ensure safety at large events. The Multi Agent Simulator (MAS) is widely used for preparing security plans that will guide responses to accidents at large events. For forming security plans, it is necessary that we simulate crowd behaviors that reflect real world observations. However, crowd behavior simulations require OD information (departure time, place of Origin, and Destination) of each agent. Moreover, from the viewpoint of protecting personal information, it is difficult to observe the complete and detailed trajectories of all pedestrians. Therefore, the OD information should be estimated from the data observed at several points, usually the number of people passing fixed points. In this paper, we propose an accurate method for estimating OD information; it has three features. First, by using Bayesian optimization (BO) which is widely used to find optimal hyper parameters in the machine learning fields, the OD information is efficiently and accurately estimated using fewer parameter searches. Second, by dividing the time window and ignoring the identity of the observed people, the parameter dimension of the OD information is reduced to yield a solvable search space. Third, by considering the time delay created by the physical separation of the observation points, we develop a more accurate objective function. Experiments evaluate the proposed method using the data collected at three events (University festival, projection-mapping event, and music live), and the accuracy with which reproduction MAS can reproduce the people flows is assessed. We also show an example of the MAS-based process used in making guidance plans to reduce crowd congestion.

In recent years, the foremost of the progress area unit having issue to adapt the advanced policies and most of the approaches required customized workflow engines. This research work focuses on projecting a new changed Model-View-Controller (MVC) framework for imposing the advanced policies to dynamic workflows. The framework Model-Operations-View-Events (MOVE) is especially supported Model-View-Controller pattern that is employed to feature the dynamic sites. The controller element in MVC framework is spitted into 2 blocks namely Operations and Events owing to artifact too several codes into the controller in MVC pattern we tend to area unit going for improved MVC framework. The main aim is to style a progress processes as a template in abstract level. The progress language is employed to implement the logic and imposing any kind of policies. Additionally to the present we tend to area unit attending to value by suggests that of learning the confidentiality and it's used permits the application-specific adaptation work running instance.

Pengembangan perangkat lunak adalah tugas kompleks dan membutuhkan adaptasi untuk mengakomodasi kebutuhan pengguna. Untuk membuat konsep dan perubahan perangkat lunak, dalam pemeliharaan, sekarang telah dikembangkan lebih mudah dalam pengembangan perangkat lunak, pola model-view-controller, yang merupakan arsitektur yang dapat membantu memfasilitasi dalam pengembangan dan pemeliharaan perangkat luna. Hal ini, karena dalam arsitektur model tiga-lapis, yaitu: tampilan dan pengontrolan dalam pembangunan dilakukan secara independen, sehingga dapat memberikan dahan dalam pengembangan dan pemeliharaan. Selain itu, arsitektur ini juga dapat melihat hal-hal yang sederhana dan menarik bagi pengguna. Software sistem on-line test adalah perangkat lunak yang memerlukan interaksi dengan pengguna, dan pemeliharaan perangkat adaptif. Karena sistem ujian on-line memerlukan pengembangan perangkat lunak untuk mengakomodasi kebutuhan ini berkembang dengan cepat. Makalah ini untuk menganalisis Model-View-Controller dan mencoba pembangunan, untuk menerapkannya dalam pengembangan perangkat lunak sistem pengujian on-line.

Spatiotemporal data mining is the core research topic of geographic information science. In the era of big data, the explosive growth of geographic spatiotemporal data puts forward an urgent demand for spatiotemporal knowledge discovery, which promotes the continuous development of spatiotemporal data mining technology. However, the universal heterogeneity and sparse distribution characteristics of spatiotemporal big data restrict the realization of spatiotemporal data mining algorithms, and significantly affect the description and analysis capabilities of natural and social complex systems. Thus, this paper focuses on the series of bottlenecks faced in the expression and application of heterogeneous and sparsely distributed spatiotemporal data. We systematically summarized the research status and existing problems of several key spatiotemporal mining tasks including missing spatiotemporal data interpolation, sparse spatiotemporal data reconstruction, and spatiotemporal state prediction, condensed four key scientific problems, and gave four corresponding solutions. The proposed methods are expected to enrich the method system in the field of spatiotemporal data mining and improve the quality and application value of spatiotemporal data modeling.