A Common Protocol for Agent-Based Social Simulation

Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.Agent-Based, Simulations, Methodology, Calibration, Validation, Sensitivity Analysis

A Common Protocol for Agent-Based Social Simulation

Traditional (i.e. analytical) modelling practices in the social sciences rely on a very well established, although implicit, methodological protocol, both with respect to the way models are presented and to the kinds of analysis that are performed. Unfortunately, computer-simulated models often lack such a reference to an accepted methodological standard. This is one of the main reasons for the scepticism among mainstream social scientists that results in low acceptance of papers with agent-based methodology in the top journals. We identify some methodological pitfalls that, according to us, are common in papers employing agent-based simulations, and propose appropriate solutions. We discuss each issue with reference to a general characterization of dynamic micro models, which encompasses both analytical and simulation models. In the way, we also clarify some confusing terminology. We then propose a three-stage process that could lead to the establishment of methodological standards in social and economic simulations.Agent-based, simulations, methodology, calibration, validation.

Towards an agent-based framework for online after-sales services

The multi-agent paradigm for building intelligent systems has gradually been accepted by researchers and practitioners in the research field of artificial intelligence. There are also attempts of adapting agents and agent-based systems for creating industrial applications and providing e-services. In this paper, we present an attempt to use agents for constructing an online after-sale services system. The system is decomposed into four major cooperative agents, and in which each agent concentrates on particular aspects in the system and expresses intelligence by using various techniques. The proposed agent-based framework for the system is presented at both the micro-level and the macro-level according to the Gaia methodology. UML notations are also used to represent some software design models. As the result of this, agents are implemented into a framework for which exploits Case-Based Reasoning (CBR) technique to fulfil real life on-line services' diagnoses and tasks

Towards Activity Context using Software Sensors

Service-Oriented Computing delivers the promise of configuring and reconfiguring software systems to address user's needs in a dynamic way. Context-aware computing promises to capture the user's needs and hence the requirements they have on systems. The marriage of both can deliver ad-hoc software solutions relevant to the user in the most current fashion. However, here it is a key to gather information on the users' activity (that is what they are doing). Traditionally any context sensing was conducted with hardware sensors. However, software can also play the same role and in some situations will be more useful to sense the activity of the user. Furthermore they can make use of the fact that Service-oriented systems exchange information through standard protocols. In this paper we discuss our proposed approach to sense the activity of the user making use of software

On Developing and Validating Dynamic Systems: Simulation Engineering.

Dynamic systems, where the behaviour is the dominant characteristic, pose engineering challenges that are often neglected in model-based software engineering. However, supporting simulation development from design models is important in demonstrating that a simulator and simulation experiments are fit for their intended purpose. In engineering agent-based simulations, observable system behaviour is built up from the behaviour of low-level components; such simulations are used as research tools in (for instance) biological systems research. We have found that domain experts can validate diagrammatic models of behaviour and accompanying text, but we need model-based software development, and ideally automatable model transformation, to maintain fitness for purpose into code and experimentation. We present an exploration of behavioural model transformation, devising and applying manual transformation guidelines to an existing, published Java Mason simulator, created using the CoSMoS approach and UML-style state diagrams. We succeed in recreating part of the class structure of the code, but also expose many issues to be overcome, in terms of what needs to be modelled to enable transformation, and how and when design decisions are taken and documented. We also identify the need to generate the creation of low-level simulation, visualisation, and data capture mechanisms, and a means to design and encode simulation experimentation

Agent-based methodology for developing agroecosystems simulations

The agent-based modeling (ABM) approach allows modeling complex systems, involving different kinds of interacting autonomous agents with heterogeneous behavior. Agro-ecosystems (ecological systems subject to human interaction) are a kind of complex system whose analysis and simulation is of interest to several disciplines (e.g. agronomy, ecology or sociology). In this context, the ABM approach appears as a suitable tool for modeling agro-ecosystems, along with a corresponding agent-oriented software engineering (AOSE) methodology for the construction of the simulation. Nevertheless, existing AOSE methodologies are general-purpose, they have not yet accomplished widespread use, and clear examples of applications to agro-ecosystems are hard to find. This thesis sets the ground for a new software development methodology for developing agro-ecosystem simulations based on the ABM approach as well as on these already existing AOSE methodologies, but tailored to tackle specific agro-ecosystem features.El enfoque de modelado basado en agentes (ABM) permite el modelado de sistemas complejos en los que interactúan diferentes tipos de agentes autónomos con comportamientos heterogéneos. Los agro-ecosistemas (sistemas ecológicos sujetos a la presencia humana) son un tipo de sistema complejo cuyo análisis y simulación resulta de interés para diversas disciplinas (ej.: agronomía, ecología o sociología). En este contexto, el enfoque ABM aparece como una herramienta adecuada para el modelado de agro-ecosistemas, junto con una correspondiente metodología de desarrollo de software también orientada a agentes (AOSE) para la construcción de dicha simulación. Si bien ya existen metodologías AOSE, éstas son de propósito general, no han logrado un amplio uso y ejemplos claros de aplicaciones a agro-ecosistemas son difíciles de encontrar. Esta tesis establece los fundamentos para crear una nueva metodología de desarrollo de software basada en el enfoque de agentes para el desarrollo de simulaciones de agro-ecosistemas, basándose en las metodologías AOSE ya existentes, pero personalizada para soportar las características específicas de los agro-ecosistemas

Methodological design and comparative evaluation of a MAS providing AmI

Researches on Ambient Intelligent and Ubiquitous Computing using wireless technologies have increased in the last years. In this work, we review several scenarios to define a multi-agent architecture that support the information needs of these new technologies, for heterogeneous domain. Our contribution consists of designing in a methodological way a Context Aware System (involving location services) using agents that can be used in very different domains. We describe all the steps followed in the design of the agent system. We apply a hybridizing methodology between GAIA and AUML. Additionally we propose a way to compare different agent architectures for Context Aware System using agent interactions. So, in this paper, we describe the assignment of weight values to agents interaction in two different MAS architectures for Context Aware problems solving different scenarios inspired in FIPA standard negotiation protocols.Publicad