Tuesday, August 24, 2010

Fusing the agent-based and Object – Field models



One of my recent works appeared as an advance online publication at the Environment and Planning B: Planning and Design. The url of the paper is: http://www.envplan.com/abstract.cgi?id=b36001

Abstract. The fusion of agent-based and geospatial models represents an exciting new synthesis for social science and economics. It has the potential to improve the theory and the practice of modelling complex real-world phenomena. Yet, to date, there has been little systematic analysis at the conceptual and logical levels of how to fuse agent-based and geospatial models for the representation and reasoning of socioeconomic phenomena. Here both sets of issues are explored. In particular, it will be argued that the development of synthetic models requires autonomous agents and flexible organisational structures that can complete their objectives while situated in a dynamic and uncertain geoenvironment represented by the concept of Elementary_geoParticle. As an example of the concept, I present a preliminary conceptual model of global energy to demonstrate the validity and possible uses of the proposed technique.

The modelling framework discussed above has been used in the ACEGES project discussed here: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1652361. A new paper is currently under review in an energy journal (i will not name the specific journal until the review process completes).

If you are interested in the topic of agent-based and geospatial models, see the gisagents blog ( http://gisagents.blogspot.com/ ) by Dr Andrew Crooks.

Simulated Scenarios of Convetional Oil Production


I will present a paper at the 4th International Conference on Computational and Financial Econometrics hosted by University of London & London School of Economics. See here for details: http://www.cfe-csda.org/cfe10/ The paper may also appear at the Computational Statistics & Data Analysis journal.


Abstract:
The ACEGES (Agent-based Computational Economics of the Global Energy System) model is an agent-based model of conventional oil production. The model accounts for four key uncertainties, namely Estimated Ultimate Recovery (EUR), estimated growth in oil demand, estimated growth in oil production and assumed peak/decline point. This work provides an overview of the ACEGES model capabilities and an example of how it can be used for long-term scenarios of conventional oil production. Because the ACEGES model has been developed using the Agent-based Computational Economics (ACE) modelling paradigm, the macro-phenomenon of interest (world oil production) grows from sets of micro-foundations (country-specific decision of oil production). The simulated data is analyzed in GAMLSS (Generalised Additive Models for Location Scale and Shape). GAMLSS is a general framework of modelling where the response variable (oil production) can have a very general (up to four parameters) distribution and all of the parameters of the distributions are modelled as linear or smooth function of the explanatory variable (e.g., time). From a methodological perspective, ACEGES and GAMLSS are applied to help leaders in government, business and civil society better understand the challenging outlook for energy through controlled computational experiments.