Computational Model Library

Modeling Personal Carbon Trading with ABM

Roman Seidl | Published Fri Dec 7 13:35:10 2018

A simulated approach for Personal Carbon Trading, for figuring out what effects it might have if it will be implemented in the real world. We use an artificial population with some empirical data from international literature and basic assumptions about heterogeneous energy demand. The model is not to be used as simulating the actual behavior of real populations, but a toy model to test the effects of differences in various factors such as number of agents, energy price, price of allowances, etc. It is important to adapt the model for specific countries as carbon footprint and energy demand determines the relative success of PCT.

(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.

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