Agent Based Simulation for Social Systems: From Modeling to Implementation
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.
KeywordsSimulation Platform Simulation Toolkit Swarm System Schedule Agent Artificial Society
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