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2009 | Buch

Multi-Agent-Based Simulation IX

International Workshop, MABS 2008, Estoril, Portugal, May 12-13, 2008, Revised Selected Papers

herausgegeben von: Nuno David, Jaime Simão Sichman

Verlag: Springer Berlin Heidelberg

Buchreihe : Lecture Notes in Computer Science

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Über dieses Buch

This book constitutes the thoroughly refereed postproceedings of the 9th International Workshop on Multi-Agent-based Simulation, MABS 2008, held in Estoril, Portugal, in May 2008. The 16 revised full papers presented have gone through two rounds of reviewing, selection, and improvement and were selected from 44 submissions; they present state-of-the-art research results in agent-based simulation and modeling. The papers are organized in topical sections on simulation of economic behaviour; modelling and simulation of social behaviou; applications; techniques, infrastructure and technologies as well as methods and methodologies.

Inhaltsverzeichnis

Frontmatter

Simulation of Economic Behaviour

Modeling Power Distance in Trade
Abstract
Agent-based computational economics studies the nature of economic processes by means of artificial agents that simulate human behavior. Human behavior is known to be scripted by cultural background. The processes of trade partner selection and negotiation work out differently in different communities. Different communities have different norms regarding trust and opportunism. These differences are relevant for processes studied in economics, especially for international trade. This paper takes Hofstede’s model of national culture as a point of departure. It models the effects on trade processes of one of the five dimensions: power distance. It formulates rules for the behavior of artificial trading agents and presents a preliminary verification of the rules in a multi-agent simulation.
Gert Jan Hofstede, Catholijn M. Jonker, Tim Verwaart
Intrusion of Agent-Based Social Simulation in Economic Theory
Abstract
This paper discusses the results of the agent based model’s cross-validation with domain experts. Subsequently, the next research step – the conceptual design of the evidence based outsourcing model – is introduced and implementation difficulties are discussed. Both models are developed in the course of the ongoing PhD research on outsourcing behaviour at financial institutions and are validated and discussed in this context.
Bogdan Werth, Scott Moss

Modelling and Simulation of Social Behaviour

A Model for HIV Spread in a South African Village
Abstract
This paper describes an agent-based simulation model of the spread of HIV/AIDS in the Sub-Saharan region. The model is part of our studying social complexity in the Sekhukhune district of the Limpopo province in South Africa. The model presents a coherent framework and identifies the essential factors agent-based modellers need to take into account when modelling HIV spread. The necessary empirical data are drawn from the villagers’ accounts during our fieldtrip to the case study region and reports from the available epidemiological and demographic literature. The results presented here demonstrate how agent-based simulation can aid in a better understanding of this complex interplay of various factors responsible for the spread of the epidemic. Although the model is specific to the case study area, the general framework described in this paper can easily be extended and adapted for other regions.
Shah Jamal Alam, Ruth Meyer, Emma Norling
Understanding Collective Cognitive Convergence
Abstract
When a set of people interact frequently with one another, they often grow to think more and more along the same lines, a phenomenon we call “collective cognitive convergence” (C3). We discuss instances of C3 and why it is advantageous or disadvantageous; review previous work in sociology, computational social science, and evolutionary biology that sheds light on C3; define a computational model for the convergence process and quantitative metrics that can be used to study it; report on experiments with this model and metric; and suggest how the insights from this model can inspire techniques for managing C3.
H. V. Parunak, T. C. Belding, R. Hilscher, S. Brueckner
Dynamics of Agent Organizations: Application to Modeling Irregular Warfare
Abstract
In this paper, we focus on computational modeling of adversarial activities and asymmetric warfare in a tactical setting. As a topic for simulation study, asymmetric warfare is an odd and ill-conditioned problem. Empirical data is scarce or one-sided, while the subject itself presents a constantly adapting and moving target that makes it a strategic priority to conceal its inner workings from the observers.
To provide an insight into the dynamics of the asymmetric conflicts, one needs to constrain the model in rigorous social-scientific concepts, including those of organization theory, theory of collective action, and social network analysis.
Our model, called NetMason, enables controlled experiments to replicate and analyze alternative policies of disruption of activities of terrorist organizations. In addition, sensitivity analysis with respect to behavioral assumptions can be easily performed.
Maksim Tsvetovat, Maciej Łatek

Applications

Using Simulation to Evaluate Data-Driven Agents
Abstract
We use simulation to evaluate agents derived from humans interacting in a structured on-line environment. The data set was gathered from student users of an adaptive educational assessment. These data illustrate human behavior patterns within the environment, and we employed these data to train agents to emulate these patterns. The goal is to provide a technique for deriving a set of agents from such data, where individual agents emulate particular characteristics of separable groups of human users and the set of agents collectively represents the whole. The work presented here focuses on finding separable groups of human users according to their behavior patterns, and agents are trained to embody the group’s behavior. The burden of creating a meaningful training set is shared across a number of users instead of relying on a single user to produce enough data to train an agent. This methodology also effectively smooths out spurious behavior patterns found in individual humans and single performances, resulting in an agent that is a reliable representative of the group’s collective behavior. Our demonstrated approach takes data from hundreds of students, learns appropriate groupings of these students and produces agents which we evaluate in a simulated environment. We present details and results of these processes.
Elizabeth Sklar, Ilknur Icke
Evaluation of Automated Guided Vehicle Systems for Container Terminals Using Multi Agent Based Simulation
Abstract
Due to globalization and the growth of international trade, many container terminals are trying to improve performance in order to keep up with demand. One technology that has been proposed is the use of Automated Guided Vehicles (AGVs) in the handling of containers within terminals. Recently, a new generation of AGVs has been developed which makes use of cassettes that can be detached from the AGV. We have developed an agent-based simulator for evaluating the cassette-based system and comparing it to a more traditional AGV system. In addition, a number of different configurations of container terminal equipment, e.g., number of AGVs and cassettes, have been studied in order to find the most efficient configuration. The simulation results suggest that there are configurations in which the cassette-based system is more cost efficient than a traditional AGV system, as well as confirming that multi agent based simulation is a promising approach to this type of applications.
Lawrence Henesey, Paul Davidsson, Jan A. Persson
MASFMMS: Multi Agent Systems Framework for Malware Modeling and Simulation
Abstract
The Internet and local area networks, which connect many personal computers, are also facilitating the proliferation of malicious programs. Modern malware takes advantage of network services like e-mail and file sharing to proliferate. Existing simulation environments use biological models or their variants for explaining the patterns of proliferation of malicious programs. This paper aims to provide a framework that enables the modeling of security threats using multi agent systems. Multi Agent Systems Framework for Malware Modeling and Simulation (MASFMMS) provides a generic environment for modeling security weaknesses and their exploitation in a computer network. We present various scenarios of exploits that are prevalent in real life and show how they can be simulated in MASFMMS.
Rohan Monga, Kamalakar Karlapalem

Techniques, Infrastructure and Technologies

Towards a Formal Semantics of Event-Based Multi-agent Simulations
Abstract
The aim of this paper is to define a non-ambiguous operational semantics for event-based multi-agent modeling and simulation, applied to complex systems. A number of features common to most multi-agent systems have been retained: 1) agent proactive as well as reactive behavior, 2) concurrency: events can arrive simultaneously to an agent, an environment or any simulated entity and the actual change only depends on the target according to the influence/reaction paradigm [1], 3) instantaneity: if reaction takes time, perception as well as information diffusion is instantaneous and should be processed separately, 4) structure dynamics: the interaction structure (who is talking to whom) changes over time, and the agents as well as any simulated entity may be created or destroyed in the course of the simulation.
For each of these features, a solution inspired by the work on \(\mathit{DEVS}\) (Discrete EVent Systems, [2]) is proposed. Proactive/reactive behavior is naturally taken into account by \(\mathit{DEVS}\). Concurrency is dealt with using \(/\!/\!\!-\!\!\mathit{DEVS}\) (in [2]), a variant of the pure \(\mathit{DEVS}\). Instantaneity is managed by distinguishing the physical events producing state transitions and the logical events realizing only perception and information diffusion. The structure dynamics is achieved by using a variant of ρ-\(\mathit{DEVS}\) (cf. [3]) where the expressiveness allows to manage hierarchical structures. The operational semantics is given as abstract algorithms and the expressive power of this formalism is illustrated on a simple example.
Jean-Pierre Müller
A User Interface to Support Dialogue and Negotiation in Participatory Simulations
Abstract
In this paper, we discuss the process of analysis and design of a user interface to support dialogue and negotiation between players of participatory simulations. The underlying context is an interdisciplinary project, named SimParc [8], about participatory management of protected areas for biodiversity conservation and social inclusion. This project is inspired by the ComMod MAS/RPG approach [6] and by recent proposals for software support for distributed role playing games, such as those by Guyot [14] and by Adamatti [1]. In this paper, we focus on the analysis and design of a user interface to ease and structure dialogue and negotiation between players, using a methodology based on semiotic engineering. Our main objective is to try to find a good balance between the necessary structuring and the spontaneity of dialog and negotiation.
Eurico Vasconcelos, Jean-Pierre Briot, Marta Irving, Simone Barbosa, Vasco Furtado
Towards Agents for Policy Making
Abstract
The process of introducing new public policies is a complex one in the sense that the behavior of society at the macro-level depends directly on the individual behavior of the people in that society and ongoing dynamics of the environment. It is at the micro-level that change is initiated, that policies effectively change the behavior of individuals. Since macro-models do not suffice, science has turned to develop and study agent-based simulations, i.e., micro-level models. In correspondence with the good scientific practice of parsimony, current ABSS models are based on agents with simple cognitive capabilities. However, the societies being modeled in policy making relate to real people with real needs and personalities, often of a multi-cultural composition. Those circumstances require the agents to be diversified to accommodate these facts.
In this positioning paper, we propose an incrementally complex model for agent reasoning that can describe the influence of policies or comparable external influences on the behavior of agents. Starting from the BDI model for agent reasoning, we discuss the effect when personality and Maslow’s hierarchy of needs are added to the model. Finally, we extend the model with a component that captures the cultural background and normative constitution of the agent.
In the paper we show how these extensions affect the filtering of the desires and intentions of the agent and the willingness of the agent to modify its behavior in face of a new policy. This way, simulations can be made that support the differentiation of behaviors in multi-cultural societies, and thus can be made to support policy makers in their decisions.
Frank Dignum, Virginia Dignum, Catholijn M. Jonker

Methods and Methodologies

A Quantitative Method for Comparing Multi-Agent-Based Simulations in Feature Space
Abstract
Comparisons of simulation results (model-to-model approach) are important for examining the validity of simulation models. One of the factors preventing the widespread application of this approach is the lack of methods for comparing multi-agent-based simulation results. In order to expand the application area of the model-to-model approach, this paper introduces a quantitative method for comparing multi-agent-based simulation models that have the following properties: (1) time series data is regarded as a simulation result and (2) simulation results are different each time the model is used due to the effect of randomness, even though the parameter setups are all the same. To evaluate the effectiveness of the proposed method, we used it for the comparison of artificial stock market simulations using two different learning algorithms. We concluded that our method is useful for (1) investigating the difference in the trends of simulation results obtained from models using different learning algorithms; and (2) identifying reliable simulation results that are minimally influenced by the learning algorithms used.
Ryota Arai, Shigeyoshi Watanabe
Deepening the Demographic Mechanisms in a Data-Driven Social Simulation of Moral Values Evolution
Abstract
The “Keep It Simple, Stupid” principle is a recommended rule for modelling complex phenomena. However, there must be a compromise between simplification and expressiveness, determined by the results produced by the model. Here we propose to gradually increase the complexity of a model, so we can improve its behaviour. This incremental “deepening” process is an attempt to approach the real phenomena, so resulting in a better model, provided that an accurate analysis reveals the right steps. As application we propose an agent-based data-driven model of the evolution of moral values in the Spanish post-modern society. We focus on improving the demographic mechanisms so that the system output follows the evolution of Spanish population. In order to do that, we raise the amount of quantitative input information of the system, improve its statistical distributions, and change the time of evolution, together with other commented changes.
Samer Hassan, Luis Antunes, Millán Arroyo
Cross-Disciplinary Views on Modelling Complex Systems
Abstract
This paper summarises work within an interdisciplinary collaboration which has explored different approaches to modelling complex systems in order to identify and develop common tools and techniques. We present an overview of the models that have been explored and the techniques that have been used by two of the partners within the project. On the one hand, there is a partner with a background in agent-based social simulation, and on the other, one with a background in equation-based modelling in theoretical physics. Together we have examined a number of problems involving complexity, modelling them using different approaches and gaining an understanding of how these alternative approaches may guide our own work. Our main finding has been that the two approaches are complimentary, and are suitable for exploring different aspects of the same problems.
Emma Norling, Craig R. Powell, Bruce Edmonds
Towards a New Approach in Social Simulations: Meta-language
Abstract
In this paper we will present a framework for bridging micro to macro emergence, macro-to-micro social causation, and the dialectic between emergence and social causation. We undertake a cultural approach for modeling communication and symbolic interaction between agents as the key element of connecting these three aspects. A cultural approach entails modeling cognitive agents who are not only capable of representing knowledge but also able to generate meanings through their experiential activities. We offer a meta-language approach allowing dynamic meaning generation during the interactions of the agents. This framework is implemented to a social simulation model. There are four important implications of the model: First, model shows a dynamic setup where agents can generate and elaborate multiplicity of meanings. Second, it exemplifies how individual mental models can interact with each other and evolve. Third, we see that a thickly coherent cultural background is not necessary for the emergence of embedded social networks, a thin coherence such as opposition maps would be sufficient to observe their dynamic formation. Fourth, exchange of meanings through successful sense-making practices generates a social anchoring process.
Raif Serkan Albayrak, Ahmet K. Süerdem
Backmatter
Metadaten
Titel
Multi-Agent-Based Simulation IX
herausgegeben von
Nuno David
Jaime Simão Sichman
Copyright-Jahr
2009
Verlag
Springer Berlin Heidelberg
Electronic ISBN
978-3-642-01991-3
Print ISBN
978-3-642-01990-6
DOI
https://doi.org/10.1007/978-3-642-01991-3

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