Multi-level agent-based modeling with the Influence Reaction principle

This paper deals with the specification and the implementation of multi-level agent-based models, using a formal model, IRM4MLS (an Influence Reaction Model for Multi-Level Simulation), based on the Influence Reaction principle. Proposed examples illustrate forms of top-down control in (multi-level) multi-agent based-simulations

The Quest for Scalability and Accuracy in the Simulation of the Internet of Things: an Approach based on Multi-Level Simulation

This paper presents a methodology for simulating the Internet of Things (IoT) using multi-level simulation models. With respect to conventional simulators, this approach allows us to tune the level of detail of different parts of the model without compromising the scalability of the simulation. As a use case, we have developed a two-level simulator to study the deployment of smart services over rural territories. The higher level is base on a coarse grained, agent-based adaptive parallel and distributed simulator. When needed, this simulator spawns OMNeT++ model instances to evaluate in more detail the issues concerned with wireless communications in restricted areas of the simulated world. The performance evaluation confirms the viability of multi-level simulations for IoT environments.Comment: Proceedings of the IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2017

Platform-level Distributed Warfare Model-based on Multi-Agent System Framework

The multi-agent paradigm has become a useful tool in solving military problems. However, one of key challenges in multi-agent model for distributed warfare could be how to describe the microcosmic  tactical warfare platforms actions. In this paper, a platform-level distributed warfare model based on multi-agent system framework is designed to tackle this challenge. The basic ideas include:  Establishing multi-agent model by mapping from tactical warfare system’s members, i.e., warfare platforms, to respective agents; performing task decomposition and task allocation by using task-tree decomposition method and improved contract net protocol model technique; and implementing simulation by presenting battlefield terrain environment analysis algorithm based on grid approach. The  simulation demonstration results show that our model provides a feasible and effective approach to supporting the abstraction and representation of microcosmic tactical actions for complex warfare system.Defence Science Journal, 2012, 62(1), pp.180-186, DOI:http://dx.doi.org/10.14429/dsj.62.96

The Social Cognitive Actor

Multi-Agent Simulation (MAS) of organisations is a methodology that is adopted in this dissertation in order to study and understand human behaviour in organisations. The aim of the research is to design and implementat a cognitive and social multi-agent simulation model based on a selection of social and cognitive theories to fulfill the need for a complex cognitive and social model. The emphasis of this dissertation is the relationship between behaviour of individuals (micro-level) in an organisation and the behaviour of the organisation as a whole (macro-level)

A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

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