Towards A Novel Unified Framework for Developing Formal, Network and Validated Agent-Based Simulation Models of Complex Adaptive Systems

Literature on the modeling and simulation of complex adaptive systems (cas) has primarily advanced vertically in different scientific domains with scientists developing a variety of domain-specific approaches and applications. However, while cas researchers are inherently interested in an interdisciplinary comparison of models, to the best of our knowledge, there is currently no single unified framework for facilitating the development, comparison, communication and validation of models across different scientific domains. In this thesis, we propose first steps towards such a unified framework using a combination of agent-based and complex network-based modeling approaches and guidelines formulated in the form of a set of four levels of usage, which allow multidisciplinary researchers to adopt a suitable framework level on the basis of available data types, their research study objectives and expected outcomes, thus allowing them to better plan and conduct their respective research case studies. Firstly, the complex network modeling level of the proposed framework entails the development of appropriate complex network models for the case where interaction data of cas components is available, with the aim of detecting emergent patterns in the cas under study. The exploratory agent-based modeling level of the proposed framework allows for the development of proof-of-concept models for the cas system, primarily for purposes of exploring feasibility of further research. Descriptive agent-based modeling level of the proposed framework allows for the use of a formal step-by-step approach for developing agent-based models coupled with a quantitative complex network and pseudocode-based specification of the model, which will, in turn, facilitate interdisciplinary cas model comparison and knowledge transfer. Finally, the validated agent-based modeling level of the proposed framework is concerned with the building of in-simulation verification and validation of agent-based models using a proposed Virtual Overlay Multiagent System approach for use in a systematic team-oriented approach to developing models. The proposed framework is evaluated and validated using seven detailed case study examples selected from various scientific domains including ecology, social sciences and a range of complex adaptive communication networks. The successful case studies demonstrate the potential of the framework in appealing to multidisciplinary researchers as a methodological approach to the modeling and simulation of cas by facilitating effective communication and knowledge transfer across scientific disciplines without the requirement of extensive learning curves

Verification and Validation of Agent Based Simulations using the VOMAS (Virtual Overlay Multi-agent System) Approach

—Agent Based Models are very popular in a number of different areas. For example, they have been used in a range of domains ranging from modeling of tumor growth, immune systems, molecules to models of social networks, crowds and computer and mobile self-organizing networks. One reason for their success is their intuitiveness and similarity to human cognition. However, with this power of abstraction, in spite of being easily applicable to such a wide number of domains, it is hard to validate agent-based models. In addition, building valid and credible simulations is not just a challenging task but also a crucial exercise to ensure that what we are modeling is, at some level of abstraction, a model of our conceptual system; the system that we have in mind. In this paper, we address this important area of validation of agent based models by presenting a novel technique which has broad applicability and can be applied to all kinds of agent-based models. We present a framework, where a virtual overlay multi-agent system can be used to validate simulation models. In addition, since agent-based models have been typically growing, in parallel, in multiple domains, to cater for all of these, we present a new single validation technique applicable to all agent based models. Our technique, which allows for the validation of agent based simulations uses VOMAS: a Virtual Overlay Multi-agent System. This overlay multi-agent system can comprise various types of agents, which form an overlay on top of the agent based simulation model that needs to be validated. Other than being able to watch and log, each of these agents contains clearly defined constraints, which, if violated, can be logged in real time. To demonstrate its effectiveness, we show its broad applicability in a wide variety of simulation models ranging from social sciences to computer networks in spatial and non-spatial conceptual models

Simulation of the research process

This paper presents first steps towards the development of a formal model of the research process. We evaluate the use of simulation as a tool for the evaluation of research strategies in nascent research organizations faced with the absence of significant data. We start by modeling the research process by using the ”Publish or Perish” paradigm, a well-known criteria of evaluation of research. We demonstrate the use of this model for researchers to evaluate the effects of selection of a particular publishing venue over time. We then perform various experiments using this basic idea. By means of various visualization techniques, we see how researchers with similar publishing policies might self-organize in the form of groups. We also evaluate the effects of giving higher weights to articles in journals and see where the effects of publishing in these venues breaks even for both top as well as average acceptance rates

SimConnector: An Approach to Testing Disaster-Alerting Systems Using Agent Based Simulation Models

The design, development and testing of intelligent disaster detection and alerting systems pose a set of non-trivial problems. Not only are such systems difficult to design as they need to accurately predict real-world outcomes using a distributed sensing of various parameters, they also need to generate an optimal number of timely alerts when the actual disaster strikes. In this paper, we propose the SimConnector Emulator, a novel approach for the testing of real-world systems using agent-based simulations as a means of validation. The basic idea is to use agent-based simulations to generate event data to allow the testing of responses of the software system to real-time events. As proof of concept, we have developed a Forest Fire Disaster Detection and Alerting System, which uses Intelligent Decision Support based on an internationally recognized Fire rating index, namely the Fire Weather Index (FWI). Results of extensive testing demonstrate the effectiveness of the SimConnector approach for the development and testing of real-time applications, in general and disaster detection/alerting systems, in particular

Verification and Validation Of An Agent-Based Forest Fire Simulation Model

In this paper, we present the verification and validation of an agent-based model of forest fires. We use a combination of a Virtual Overlay Multi-Agent System (VOMAS) validation scheme with Fire Weather Index (FWI) to validate the forest fire Simulation. FWI is based on decades of real forest fire data and is now regarded as a standard index for fire probability with wide usage across Canada, New Zealand and Australia. VOMAS approach allows for flexible validation of agent-based simulation models. In the current work, it is used in the form of a simulation of a randomly deployed Wireless Sensor Network for forest monitoring. Here, each virtual "sensor" agent uses FWI to calculate fire probability and compares it with the simulation model. VOMAS verification and validation methodology for agent-based models allows for interactive design of Agent-Based Models involving both the Simulation Specialists as well as the Subject Matter Experts. The presented simulation model also uses weather parameters such as wind speed, rain, snow to calculate Indices such as Fire Weather Index (FWI), Build Up Index (BUI) and Initial Spread Index (ISI) in real time. We also study the effects of fires on the life of simulated VOMAS sensors. Using extensive simulations, we demonstrate the effectiveness and ease of use of VOMAS based Validation

A new hybrid agent-based modeling & simulation decision support system for breast cancer data analysis

In this paper, we present a novel technique of building hybrid decision support systems which integrates traditional decision support systems with agent based models for use in breast cancer analysis for better prediction and recommendation. Our system is based on using queries from data (converted to a standardized electronic template) to provide for simulation variables in an agent-based model. The goal is to develop an ICT tool to assist non-specialist biologist researcher users in performing analysis of large amounts of data by applying simple simulation techniques. To demonstrate the effectiveness of this novel decision support system, an extensive breast cancer data collection exercise was carried out with the support of Hospitals in a previously unexplored region. The collected data was subsequently integrated in an electronic medical record filing system for patients. We also demonstrate the application of agent based modeling and simulation techniques for building simulation models of tumor growth and treatment. Our proposed decision support system also provides a comprehensive query tool which facilitates the use of retrieved data in statistical tools for subsequent interpretation and analysis