Towards a standard model for research in agent-based modeling and simulation
- Published
- Accepted
- Subject Areas
- Agents and Multi-Agent Systems, Scientific Computing and Simulation, Theory and Formal Methods
- Keywords
- agent-based modeling, standard model, statistical analysis of simulation output, ODD
- Copyright
- © 2015 Fachada et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Towards a standard model for research in agent-based modeling and simulation. PeerJ PrePrints 3:e1440v1 https://doi.org/10.7287/peerj.preprints.1440v1
Abstract
Agent-based modeling (ABM) is a bottom-up modeling approach, where each entity of the system being modeled is uniquely represented as an independent decision-making agent. ABMs are very sensitive to implementation details. Thus, it is very easy to inadvertently introduce changes which modify model dynamics. Such problems usually arise due to the lack of transparency in model descriptions, which constrains how models are assessed, implemented and replicated. In this paper, we present PPHPC, a model which aims to serve as a standard in agent based modeling research, namely, but not limited to, conceptual model specification, statistical analysis of simulation output, model comparison and parallelization studies. This paper focuses on the first two aspects (conceptual model specification and statistical analysis of simulation output), also providing a canonical implementation of PPHPC. The paper serves as a complete reference to the presented model, and can be used as a tutorial for simulation practitioners who wish to improve the way they communicate their ABMs.
Author Comment
This is a submission to PeerJ Computer Science for review.
Supplemental Information
PRNG seeds used for the NetLogo replications
Table S1. PRNG seeds used for the NetLogo replications. Each seed was obtained by taking the MD5 checksum of replication number and converting the resulting hexadecimal string to a 32-bit integer (the maximum precision accepted by NetLogo).
Statistics and distributional analysis of the selected focal measures for n = 30 replications of the PPHPC model
Tables S2.1 to S2.10. Statistics and distributional analysis of the selected focal measures for n = 30 replications of the PPHPC model for all the model size and parameter set combinations.
Outputs of 30 replications for all model sizes and parameter set 1
Dataset 1. Outputs of 30 replications for all model sizes and parameter set 1. Each text file corresponds to one replication. Columns correspond to outputs in the following order: prey population, predator population, available cell-bound food, mean prey energy, mean predator energy, mean value of the grid cells C state variable. Rows correspond to iterations.
Outputs of 30 replications for all model sizes and parameter set 2
Dataset 2. Outputs of 30 replications for all model sizes and parameter set 2. Each text file corresponds to one replication. Columns correspond to outputs in the following order: prey population, predator population, available cell-bound food, mean prey energy, mean predator energy, mean value of the grid cells C state variable. Rows correspond to iterations.