MAS and Social Simulation: A Suitable Commitment

Whilst simulation has been common in other areas for some time, it has only gained significant prominence in the social sciences during the last two decades. In 1988, Ostrom called simulation “The Third Symbol System” in the context of social psychology. By this she meant that simulation stood alongside natural language and mathematics as a way to represent theories about social cognition. Later, in 1997, Axelrod stated that simulation was a third way of doing science, in particular social science.

2015

Dottorato di ricerca in “Informatica” Ciclo XVII Supervisori:

ERN: Simulation Methods (Topic), 2006

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...

… & Mathematical Organization …, 2001

A lengthy and intensive debate about the role of sociology in agent based social simulation dominated the email list simsoc@jiscmail.ac.uk during the autumn of 2000. The debate turned on the importance of models being devised to capture the properties of whole social systems and whether those properties should determine agent behaviour or, conversely, whether the properties of social systems should emerge from the behaviour and interaction of the agents and, if so, how that emergence should be represented. The positions of four of the main protagonists concerned specifically with the modelling issues are reprised and extended in this symposium.

Workshop From Objects to Agents, 2006

This paper introduces some considerations about simulation practice and a schema of the models that are implic- itly and explicitly involved in a Multi-Agent Based Simulation (MABS). The aim of this work is to set simulation inside scientific framework. In order to do that we give an interpretation of the levels that compound a simulation and that constitute different kinds

Lecture Notes in Computer Science, 2006

This paper presents experimental results of our model-driven approach to agent based simulation. According to this, the development process for agent based simulation should focus on modeling rather than implementation (i.e., programming on some concrete agent simulation platform). This requires the use of transformation tools from simulation models to implementation code. Describing social phenomena with a visual, high-level modeling language and implementing the simulation in this way should facilitate the use of toolkits by experts in social sciences without a deep knowledge of programming concerns. This simulation approach is supported here by the INGENIAS Development Kit (IDK), which provides a model editor for multi-agent systems, and code generation support. To validate the transformation mechanism, we have modeled a concrete social system with the INGENIAS agent-oriented modeling language, and generated two independent implementations for two different platforms (Repast and Mason simulation toolkits). This experimentation shows the feasibility of the model driven implementation approach and has enabled the study of facilities provided by simulation toolkits that can have impact on the transformation process, in particular, the scheduling techniques. Also, comparing the simulation results of the case study with the original work and between implementations has led us to discover biases introduced by simulation mechanisms that can be found in most simulation platforms.

2010

Agent-based simulation is being recognized as a useful tool for the study of social systems. It is based on the idea that agents can be used as a good abstraction of members of a society, and by simulating their interactions, observe the emergent behavior. Usually, agent-based models for social simulation are rather simple, but there are more and more works that try to apply this technique for rather complex systems, both in the typology of the agents and their relationships, and in scalability.

The Fifth IASTED …, 2005

This paper discusses a multi-agent simulation theory which is serving as a formal specification to guide the development of a multi-agent simulation platform. We have extended an existing simulation language: GLIDER, with abstractions to model systems where autonomous entities (agents) perceive and act upon their environments. Thus far, we have completed the development of the platform that implements the theory and we are now applying it to the study of multi-agent systems. In particular, an Implementation on Biocomplexity is briefly discussed in the paper.

2012

Computational social science and in particular agent-based social simulation continue to gain momentum in the academic community. Social network analysis enjoys even more popularity. They both have much in common. In agent-based models, individual interactions are simulated to generate social patterns of all kinds, including relationships that can then be analyzed by social network analysis. This chapter describes and discusses the role of agent-based modeling in the generative-analytical part of this symbiosis.

Agent-Based Social Systems, 2005

ABSS-Agent-Based Social Systems This series is intended to further the creation of the science of agent-based social systems, a field that is establishing itself as a transdisciplinary and cross-cultural science. The series will cover a broad spectrum of sciences,