Abstract
There is little research concerning comparisons and combination of System Dynamics Simulation (SDS) and Agent Based Simulation (ABS). ABS is a paradigm used in many levels of abstraction, including those levels covered by SDS. We believe that the establishment of frameworks for the choice between these two simulation approaches would contribute to the simulation research. Hence, our work aims for the establishment of directions for the choice between SDS and ABS approaches for immune system-related problems. Previously, we compared the use of ABS and SDS for modelling agents’ behaviour in an environment with no movement or interactions between these agents. We concluded that for these types of agents it is preferable to use SDS, as it takes up less computational resources and produces the same results as those obtained by the ABS model. In order to move this research forward, our next research question is: if we introduce interactions between these agents will SDS still be the most appropriate paradigm to be used? To answer this question for immune system simulation problems, we will use, as case studies, models involving interactions between tumour cells and immune effector cells. Experiments show that there are cases where SDS and ABS can not be used interchangeably, and therefore, their comparison is not straightforward.
Highlights
The current scenario in the simulation field presents paradigms that allow us to build simulation models for various domains
Our goal is to determine which scenarios for immune system simulations inside the System Dynamics Simulation (SDS)/Agent-Based Simulation (ABS) intersection would benefit from SDS resources and those that are more suitable for ABS
For the ABS, the number of effector cells decreases until a value close to zero while the tumour cells numbers vary in time differently from the SDS results
Summary
The current scenario in the simulation field presents paradigms that allow us to build simulation models for various domains. Some of the important simulation approaches are System Dynamics Simulation (SDS), Agent-Based Simulation (ABS), Discrete Event Simulation (DES) and Dynamic Systems (DS)[3]. New research combines these methods and defines frameworks for the usage of each paradigm. There is already work comparing SDS/DES, DES/ABS as well as their combinations. There is few research on the comparison and combination of SDS and ABS [8]. Our research aims at establishing a framework for the development of simulations involving the choice between
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