Studies on word-of-mouth identify two behaviors leading to transmission of information between individuals: proactive transmission of information, and information seeking. Individuals who are aware might be curious of it and start seeking for information; they might find around them the expertise held by another individual. Field studies indicate individuals do not adopt an innovation if they don’t hold the corresponding expertise. This model describes this information seeking behavior, and enables the exploration of the dynamics which emerges out of it.
(PLEASE DO NOT DOWNLOAD. This simulation is not user-friendly. UI has been removed for faster experimentation. An interactive version will be uploaded when the paper is accepted.)
Simulations of Public Goods Games (PPGs) are usually in discrete time (one shot decisions about contributions to public goods). To our knowledge, this is the first simulation of continuous-time PGGs (where participants can change contributions at any time) which are much harder to realise within both laboratory and simulation environments. The simulation is for a journal article submitted to JASSS (in review): “Tuong Manh Vu (2018). Overcoming the Hurdles of Continuous-Time Public Goods Games with A Simulation-Based Approach.”
The paper shows how to apply our recently developed ABOOMS (Agent-Based Object-Oriented Modelling and Simulation) framework to create simulation-supported continuous-time PGG studies. The ABOOMS framework utilizes Software Engineering techniques to support the development at macro level (considering the overall study lifecycle) and at micro level (considering individual steps related to simulation model development). The case study shows that outputs from the simulation-supported continuous-time PGG generate dynamics 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.
Model for evaluating various ambulance dispatching policies of an equity constrained emergency medical services under bounded rationality.
This is an agent-based model of peer review built on the following three entities: papers, scientists and conferences. The model has been implemented on a BDI platform (Jason) that allows to perform both parameter and mechanism exploration.