新的RoboCup救援仿真分区消防策略

在RoboCup救援仿真的消防策略中,火势蔓延的控制对救援的效果有着重要的作用。大多数队伍采用基于单个建筑的各种指标的单目标选择法,该方法在着火建筑较多或者火势蔓延快时难以对火势进行有效控制。提出一种新的基于密度聚类的分区方法,根据火势蔓延速度将所有建筑进行聚类分析形成建筑簇并分开成为不同的区域,然后综合建筑的属性作为权值选择目标区域和灭火建筑,从而有效地控制火灾的蔓延甚至将火灾完全扑灭。最后通过仿真实验和比赛验证了该方法的有效性。     

An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster

A key activity in emergency management is planning and preparation for disaster. If the right safety measures are implemented beforehand, harmful effects can be significantly mitigated. However, evaluation and selection of effective measures is difficult due to the numerous scenarios that exist in most emergency environments coupled with the high associated cost of testing such scenarios. An agent-based system employs a computational model of autonomous interacting agents in an environment with the purpose of assessing the emergent behavior of the group. This paper presents a prototype of a computer simulation and decision support system that uses agent-based modeling to simulate crowd evacuation in the presence of a fire disaster and provides for testing of multiple disaster scenarios at virtually no cost. The prototype is unique in the current literature as it is specifically designed to simulate a concert venue setting such as a stadium or auditorium and is highly configurable allowing for user definition of concert venues with any arrangement of seats, pathways, stages, exits, and people as well as the definition of multiple fires with fire and smoke dynamics included.     

ERT-VR: an immersive virtual reality system for emergency rescue training

Virtual reality technology offers a cost effective means to train emergency rescuers, which is an urgent task on account of the increasing terrorist acctivities. An immersive virtual reality system called ERT-VR is introduced. In ERT-VR, the display system based on stereoscopic projectors is used to train the emergency rescue commanders. The members of the operational teams use head-mounted display as the display system. The 3D scenario creator is the most important unit in ERT-VR. Instructors assign a specific training scenario to the trainees by using the scenario creator. Trainees take on the role of the characters in the training scenario and control their actions and ultimately the scenario outcomes. All the actions are recorded into the database system and can be replayed anytime. The potential of each trainee is evaluated by an expert system.     

Hidden roles of the train driver: A challenge for metro automation

In the year 2014, the Helsinki Metro is planned to be fully automated. This automation means that the metro trains will be computer-driven and monitored remotely from a stationary control room. To investigate the challenges related to this scenario, we decided to study the ways in which the current train drivers contribute to the metro system. We conducted three separate but interrelated studies, which were based on the Core-Task Analysis method. Our results suggest that there is much more to driving the metro train than meets the eye. The drivers do not only operate the train on track and its doors at stations, but they also contribute to a variety of other important, albeit more hidden, functions in the metro system. For example, the drivers anticipate, observe, interpret, and react to events in the surrounding environment. Furthermore, they are a significant interaction link between different actors of the metro system. Our conclusion is that if the identified critical roles of the drivers are not accounted for, a migration to a fully automated metro system can affect the quality of service and raise safety issues. In addition to automated metros, the results of this research can be applicable to automation implementations also in other domains.     

Repast:基于Agent建模仿真的可扩展平台

建模仿真平台为基于Agent建模理论和方法的研究创造了条件.在研究当前流行的基于Agent建模仿真平台不足的基础之上,介绍了一种新的基于Agent建模仿真平台Repast,详细阐述了该平台的设计目标、框架结构及运行机制等内容,并结合一个实例简要说明了Repast模型的设计与实现过程.该平台移植性和可扩展性强,使用方便,易于学习,方便了应用基于Agent建模仿真方法对复杂适应系统及复杂性的研究及探索,同时也为复杂适应系统的研究提供新的思路.     

An agent-based simulation model for analyzing the governance of the Brazilian Financial System

Regulation can play an important role in effectively managing systemic risk while providing accountability to all affected governments. IMF points out weak governance structures as one of the main causes for financial/economical crisis. However, research in this area is still limited. One of the reasons is the inherent complexity of the public sector governance notion. In this research, the regulatory governance of the financial sector is conceived as a complex system, in which governance is perceived as a phenomenon resulting from the interactions among all the actors that influence or are influenced by regulatory activities within the financial sector. An agent-based simulation was developed to analyze and evaluate the emergent behaviors from the governance in the Brazilian finance sector under different macroeconomics variables and different attitudes, perceptions and desires of economic and political actors. The agent-based model is combined with an econometric model, which is intended to characterize the macroeconomic environment. The regulatory environment is modeled by computational agents using BDI (beliefs–desires–intentions) architecture. The agents have beliefs about their environment and desires they want to satisfy, thus leading them to create intentions to act. The agents’ behavior was modeled using fuzzy rules built by means of content analysis of newspapers and in-depth interviews with experts from the financial area. Computational experiments demonstrate the potential of the agent-based model simulation in the study of complex environments involving regulatory governance.     

Implementing a hybrid simulation model for a Kanban-based material handling system

Plant floor material handling is a loose loop in most assembly plants. Simulation offers a quick, controllable and tunable approach for prototyping complex material handling processes in manufacturing environments. This paper proposes a hybrid simulation approach, using both discrete event and agent-based technologies, to model complex material handling processes in an assembly line. A prototype system is implemented using a commercial multi-paradigm modeling tool. In this prototype, JIT principles are applied to both the production and the material handling processes. The system performance is evaluated and system optimization directions are suggested. The proposed hybrid modeling approach facilitates the implementation of a responsive and adaptive environment in that various “what-if” scenarios can be simulated under different simulation configurations and real-time situations.     

Agent-based modelling and simulation for the analysis of social patterns

Agent-based modelling facilitates the implementation of tools for the analysis of social patterns. This comes from the fact that agent related concepts allow the representation of organizational and behavioural aspects of individuals in a society and their interactions. An agent can characterize an individual with capabilities to perceive and react to events in the environment, taking into account its mental state (beliefs, goals), and to interact with other agents in its social environment. There are already tools to perform agent-based social simulation but these are usually hard to use by social scientists, as they require a good expertise in computer programming. In order to cope with such difficulty, we propose the use of agent-based graphical modelling languages, which can help to specify social systems as multi-agent systems in a more convenient way. This is complemented with transformation tools to be able to analyse and derive emergent social behavioural patterns by using the capabilities of existing simulation platforms. In this way, this framework can facilitate the specification and analysis of complex behavioural patterns that may emerge in social systems.     

The emergence of a Fintech Ecosystem: A case study of the Vizag Fintech Valley in India

Fintech ecosystems (FE) are characterized by heterogeneous, non-linear, dynamic and complex network of agents that interact with each other to provide a wide array of financial products and services to end customers. With the rise of myriad complementary technologies, the complexity of Fintech ecosystems is increasing exponentially as new players are emerging and new connections are formed. Despite the widespread attention Fintech ecosystems have attracted from both academia and practice, rather little is known about how such an ecosystem emerge. Toward addressing this knowledge gap, this research paper draws on complex adaptive systems (CASs) theory to examine the emergence of a global self-sustaining ecosystem: The “Fintech Valley” in Vizag, India. In doing so, our findings offer insights into the dynamics of FE emergence that is transforming the financial landscape globally, and may be helpful to practitioners who are looking to effect organization-wide cultural change and the 'compliant by design' approach.     

ManufAg: a multi-agent-system framework for production control of complex manufacturing systems

In this paper, we present a framework for the implementation of multi-agent-systems for production control of complex manufacturing systems. We present the results of a requirement analysis for production control systems for complex manufacturing systems; then we describe the framework design criteria. Our framework supports the inclusion of distributed hierarchical decision-making schemes into the production control. Furthermore, in order to increase the coordination abilities of multi-agent-systems, we follow the decision-making and staff agent architecture suggested in the PROSA reference architecture. We indicate the usage of the framework for designing and implementing an agent-based production control system for semiconductor manufacturing processes in a case study.     

Agent-based simulation of electricity markets: a survey of tools

Agent-based simulation has been a popular technique in modeling and analyzing electricity markets in recent years. The main objective of this paper is to study existing agent-based simulation packages for electricity markets. We first provide an overview of electricity markets and briefly introduce the agent-based simulation technique. We then investigate several general-purpose agent-based simulation tools. Next, we review four popular agent-based simulation packages developed for electricity markets and several agent-based simulation models reported in the literature. We compare all the reviewed packages and models and identify their common features and design issues. Based on the study, we describe an agent-based simulation framework for electricity markets to facilitate the development of future models for electricity markets.     

复杂系统基于Agent的建模与仿真设计模式及软件框架

提出了一种基于Agent的建模与仿真设计模式——ABMS设计模式，阐述了ABMS设计模式的主要内容。该模式的提出有利于在建模与仿真领域以及软件开发界之间建立关于ABMS的对话联系与交流。然后设计了一种包含仿真服务模型ServerAgent和仿真模型结构SimAgent的ABMS分布仿真框架，该框架将最大限度实现仿真重用，并将支持大规模的基于Agent的复杂系统的仿真，包括军事对抗以及天战系统的仿真。该框架部分借鉴了HLA的思想，其中的ServerAgent提供底层的通用仿真服务。     

Analysis of crime patterns through the integration of an agent-based model and a population microsimulation

In recent years, criminologists have become interested in understanding crime variations at progressively finer spatial scales, right down to individual streets or even houses. To model at these fine spatial scales, and to better account for the dynamics of the crime system, agent-based models of crime are emerging. Generally, these have been more successful in representing the behaviour of criminals than their victims. In this paper it is suggested that individual representations of criminal behaviour can be enhanced by combining them with models of the criminal environment which are specified at a similar scale. In the case of burglary this means the identification of individual households as targets. We will show how this can be achieved using the complementary technique of microsimulation. The work is significant because it allows agent-based models of crime to be refined geographically (to allow, for example, individual households with varying wealth or occupancy measures) and leads to the identification of the characteristics of individual victims.     

Responding to a fire emergency in a virtual environment: different patterns of action for different situations

This paper presents an experimental study of participants' response to the sudden appearance of a fire emergency in a virtual environment (VE) and of the adaptivity of their response pattern. A VE has been built in which participants meet two situations: first an explorative navigation and afterwards a hurried escape from the unexpected outbreak of fire. Fire intensity and participants' distance from the exit at the outbreak of fire have been varied as well, to create different degrees of danger and different degrees of difficulty in the task of leaving the premises. Participants' action has been collected automatically for quantitative analysis by registering each individual activation of the interaction devices (a triple button joystick). In addition, the movements in both virtual and real environment of additional groups of participants have been videorecorded for qualitative analysis. Results show that the appearance of the fire emergency triggers important changes in the way people move in the VE, and that such changes are all adaptive responses to an emergency situation. In conclusion, people show recognition of a dangerous situation in a VE and readily produce adaptive responses, making the VE suitable for emergency simulations and for use as an effective training tool.     

A systematic approach for new service concept generation: Application of agent-based simulation

In new service development (NSD), a concept design that influences the direction of other activities is considered as a crucial stage. Although several methods exist, most of them cannot reflect responses of future potential customers because they assume that customers have the same responses in the future. Therefore, by using agent-based simulation (ABS) that can understand the future status of a service system, this paper suggests a new approach to creating the most promising service concept. The proposed approach considers the future trends of various customer responses and service concept strategies of firms by using ABS, generating a more accurate concept. By applying the suggested approach to a healthcare industry, its practicability and utility are verified. The novel approach based on the agent-based simulation method, which has customer, service provider, and competitor agents, is expected to be useful for service providers in a competitive market.     

A high performance framework for modeling and simulation of large-scale complex systems

Due to the quick advances in the scale of problem domain of complex systems under investigation, the complexity of multi-input component models used to construct logical processes (LP) has significantly increased. High-performance computing technologies have therefore been extensively used to enable parallel simulation execution. However, the traditional multi-process parallel method (MPM) executes LPs in parallel on multi-core platforms, which ignores the intrinsic parallel capabilities of multi-input component models. In this study, a vectorized component model (VCM) framework has been proposed. The design aims to better utilize the parallelism of multi-input component models. A two-level composite parallel method (CPM) has then been constructed within the framework, which can sustain complex system simulation applications consisting of multi-input component models. CPM first employs MPM to dispatch LPs onto a multi-core computing platform. It then maps VCMs to the multiple-core platform for parallel execution. Experimental results indicate that (1) the proposed VCM framework can better utilize the parallelism of multi-input component models, and (2) CPM can significantly improve the performance comparing to the traditional MPM. The results also show that CPM can effectively cope with the size and complexity of complex simulation applications with multi-input component models.     

Multi-driver agent-based traffic simulation systems for evaluating the effects of advanced driver assistance systems on road traffic accidents

A recent investigation revealed that there is a substantiated need for the development of a micro-simulation system designed for traffic safety assessment. This paper describes the development of a road traffic simulation system, which uses a ‘nanoscopic model’ of driver behaviour and an integrated analysis-evaluation system designed for traffic safety assessment. The primary focus is on estimating the effects of an advanced driver assistance system thereby reducing traffic accidents. The effectiveness and validity of the present system are demonstrated through comparison with measured traffic data. This paper also proposes algorithms embedded in a ‘driver-agent’, for recognising driver’s intentions regarding choosing steering-control modes, lateral control tasks, and the driving mood. This is because the driver assistance systems need to recognise the driver’s intention when choosing steering-control. The results of a simulation study, using the data drawn from actual driving, show that the systems would achieve a high recognition capability. As an example of how driving mood recognition applies to driver assistance systems, an advanced steering system and the adaptability to the driver’s mood, have also been presented.     

一类复杂系统的自适应控制

对于具有相似性的一类不确定复杂系统,应用高阶神经网络逼近各个子系统的互联项,设计了控制器,即提出了难以解决的互联项问题的高阶神经网络表示方法．该方法通过在线调节神经网络的权值来确保闭环系统的稳定性．由于复杂系统的结构相似性,降低了控制器设计过程中的计算量,使得工程上较易实现．仿真算例表明了所提出方法的有效性.