INVESTIGATION INTO GAME-BASED CRISIS SCENARIO MODELLING AND SIMULATION SYSTEM

A crisis is an infrequent and unpredictable event. Training and preparation process requires tools for representation of crisis context. Particularly, crisis events consist of different situations, which can occur at the same time combining into complex situation and becoming a challenge in coordinating several crisis management departments. In this regards, disaster prevention, preparedness and relief can be conceptualized into a design of hypothetical crisis game. Many complex tasks during development of emergency circumstance provide an opportunity for practitioners to train their skills, which are situation analysis, decision-making, and coordination procedures. While the training in physical workouts give crisis personal a hand-on experience in the given situation, it often requires a long time to prepare with a considerable budget. Alternatively, computational framework which allows simulation of crisis models tailoring into crisis scenario can become a cost-effective substitution to this study and training. Although, there are several existing computational toolsets to simulate crisis, there is no system providing a generic functionality to define crisis scenario, simulation model, agent development, and artificial intelligence problem planning in the single unified framework. In addition, a development of genetic framework can become too complex due to a multi-disciplinary knowledge required in each component. Besides, they have not fully incorporated a game technology toolset to fasten the system development process and provide a rich set of features and functionalities to these mentioned components. To develop such crisis simulation system, there are several technologies that must be studied to derive a requirement for software engineering approach in system’s specification designs. With a current modern game technology available in the market, it enables fast prototyping of the framework integrating with cutting-edge graphic render engine, asset management, networking, and scripting library. Therefore, a serious game application for education in crisis management can be fundamentally developed early. Still, many features must be developed exclusively for the novel simulation framework on top of the selected game engine. In this thesis, we classified for essential core components to design a software specification of a serious game framework that eased crisis scenario generation, terrain design, and agent simulation in UML formats. From these diagrams, the framework was prototyped to demonstrate our proposed concepts. From the beginning, the crisis models for different disasters had been analysed for their design and environment representation techniques, thus provided a choice of based simulation technique of a cellular automata in our framework. Importantly, a study for suitability in selection of a game engine product was conducted since the state of the art game engines often ease integration with upcoming technologies. Moreover, the literatures for a procedural generation of crisis scenario context were studied for it provided a structure to the crisis parameters. Next, real-time map visualization in dynamic of resource representation in the area was developed. Then the simulation systems for a large-scale emergency response was discussed for their choice of framework design with their examples of test-case study. An agent-based modelling tool was also not provided from the game engine technology so its design and decision-making procedure had been developed. In addition, a procedural content generation (PCG) was integrated for automated map generation process, and it allowed configuration of scenario control parameters over terrain design during run-time. Likewise, the artificial planning architecture (AI planning) to solve a sequence of suitable action toward a specific goal was considered to be useful to investigate an emergency plan. However, AI planning most often requires an offline computation with a specific planning language. So the comparison study to select a fast and reliable planner was conducted. Then an integration pipeline between the planner and agent was developed over web-service architecture to separate a large computation from the client while provided ease of AI planning configuration using an editor interface from the web application. Finally, the final framework called CGSA-SIM (Crisis Game for Scenario design and Agent modelling simulation) was evaluated for run-time performance and scalability analysis. It shown an acceptable performance framerate for a real-time application in the worst 15 frame-per-seconds (FPS) with maximum visual objects. The normal gameplay performed capped 60 FPS. At same time, the simulation scenario for a wildfire situation had been tested with an agent intervention which generated a simulation data for personal or case evaluation. As a result, we have developed the CGSA-SIM framework to address the implementation challenge of incorporating an emergency simulation system with a modern game technology. The framework aims to be a generic application providing main functionality of crisis simulation game for a visualization, crisis model development and simulation, real-time interaction, and agent-based modelling with AI planning pipeline

Best-subset Selection for Complex Systems using Agent-based Simulation

It is difficult to analyze and determine strategies to control complex systems due to their inherent complexity. The complex interactions among elements make it difficult to develop and test decision makers' intuition of how the system will behave under different policies. Computer models are often used to simulate the system and to observe both direct and indirect effects of alternative interventions. However, many decision makers are unwilling to concede complete control to a computer model because of the abstractions in the model, and the other factors that cannot be modeled, such as physical, human, social and organizational relationship constraints. This dissertation develops an agent-based simulation (ABS) model to analyze a complex system and its policy alternatives, and contributes a best-subset selection (BSS) procedure that provides a group of good performing alternatives to which decision makers can then apply their subject and context knowledge in making a final decision for implementation. As a specific example of a complex system, a mass casualty incident (MCI) response system was simulated using an ABS model consisting of three interrelated sub-systems. The model was then validated by a series of sensitivity analysis experiments. The model provides a good test bed to evaluate various evacuation policies. In order to find the best policy that minimizes the overall mortality, two ranking-and-selection (R&S) procedures from the literature (Rinott (1978) and Kim and Nelson (2001)) were implemented and compared. Then a new best-subset selection (BSS) procedure was developed to efficiently select a statistically guaranteed best-subset containing all alternatives that are close enough to the best one for a pre-specified probability. Extensive numerical experiments were organized to prove the effectiveness and demonstrate the performance of the BSS procedure. The BSS procedure was then implemented in conjunction with the MCI ABS model to select the best evacuation policies. The experimental results demonstrate the feasibility and effectiveness of our agent-based optimization methodology for complex system policy evaluation and selection

RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

Advances in Reinforcement Learning

Reinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic

Assessing vulnerability and modelling assistance: using demographic indicators of vulnerability and agent-based modelling to explore emergency flooding relief response

Flooding is a significant concern for much of the UK and is recognised as a primary threat by most local councils. Those in society most often deemed vulnerable: the elderly, poor or sick, for example, often see their level of vulnerability increase during hazard events. A greater knowledge of the spatial distribution of vulnerability within communities is key to understanding how a population may be impacted by a hazard event. Vulnerability indices are regularly used – in conjunction with needs assessments and on-the-ground research – to target service provision and justify resource allocation. Past work on measuring and mapping vulnerability has been limited by a focus on income-related indicators, a lack of consideration of accessibility, and the reliance on proprietary data. The Open Source Vulnerability Index (OSVI) encompasses an extensive range of vulnerability indicators supported by the wider literature and expert validation and provides data at a sufficiently fine resolution that can identify vulnerable populations. Findings of the OSVI demonstrate the potential cascading impact of a flood hazard as it impacts an already vulnerable population: exacerbating pre-existing vulnerabilities, limiting capabilities and restricting accessibility and access to key services. The OSVI feeds into an agent-based model (ABM) that explores the capacity of the British Red Cross (BRC) to distribute relief during flood emergencies using strategies based upon the OSVI. A participatory modelling approach was utilised whereby the BRC were included in all aspects of the model development. The major contribution of this work is the novel synthesis of demographics analysis, vulnerability mapping and geospatial simulation. The project contributes to the growing understanding of vulnerability and response management within the NGO sector. It is hoped that the index and model produced will allow responder organisations to run simulations of similar emergency events and adjust strategic response plans accordingly

COIN@AAMAS2015

COIN@AAMAS2015 is the nineteenth edition of the series and the fourteen papers included in these proceedings demonstrate the vitality of the community and will provide the grounds for a solid workshop program and what we expect will be a most enjoyable and enriching debate.Peer reviewe

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area