Paper Info
Title
ABOOMS: Overcoming the Hurdles of Continuous-Time Public Goods Games with a Simulation-Based Approach.
Abstract
Public Goods Games (PGGs) are a standard experimental economic approach to studying cooperative behaviour. There are two types of games: discrete-time and continuous-time PGGs. While discrete-time PGGs (one-shot decisions about contributions to public goods) can be easily done as lab experiments, continuous-time PGGs (where participants can change contributions at any time) are much harder to realise within a lab environment. This is mainly because it is difficult to consider events happening in continuous time in lab experiments. Simulation offers an opportunity to support real-world lab experiments and is well suited to explore continuous-time PGGs. In this paper, we show how to apply our recently developed ABOOMS (Agent-Based Object-Oriented Modelling and Simulation) development framework to create models for simulation-supported continuous-time PGG studies. The ABOOMS framework utilizes Software Engineering techniques to support the development at the macro level (considering the overall study lifecycle) and at the micro level (considering individual steps related to simulation model development). Our case study shows that outputs from the simulation-supported continuous-time PGG generate dynamics that do not exist in discrete-time setting, highlighting the fact that it is important to study both, discrete and continuous-time PGGs.
Year
DOI
Venue
2019
10.18564/jasss.3995
JASSS-THE JOURNAL OF ARTIFICIAL SOCIETIES AND SOCIAL SIMULATION
Keywords
Field
DocType
Agent-Based Modelling and Simulation,Continuous-Time Public Goods Game,Software Engineering Agent-Based Computational Economics,Object-Oriented Analysis and Design
Public good,Computer science,Agent-based computational economics,Macro,Management science,Object-oriented analysis and design
Journal
Volume
Issue
ISSN
22
2
1460-7425
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Tuong Manh Vu101.35
Christian Wagner25618.39
Peer-Olaf Siebers318627.03