Ecosimnet: A framework for ecological simulations

• Type: Article in International Conference Proceedings Book
• Date: 2009

Authors

António Pereira (Author) FEUP; Luís Paulo Reis (Author) FEUP; Pedro Duarte (Author) Other

Conference proceedings International

Title: 23RD EUROPEAN CONFERENCE ON MODELLING AND SIMULATION (ECMS 2009)

Pages: 219-225

23rd European Conference on Modelling and Simulation (ECMS)

Madrid, SPAIN, JUN 09-12, 2009

Indexing

ISI Proceedings

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

INSPEC

Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Technological sciences > Engineering > Simulation engineering ; Natural sciences > Environmental science > Natural resources management > Coastal zone management

Other information

Authenticus ID: P-003-SZ8

DOI: 10.7148/2009-0219-0225

Abstract (EN): Simulating ecological models is always a difficult task, not only because of its complexity but also due to the slowness associated with each simulation run as more variables and processes are incorporated into the complex ecosystem model. The computational overhead becomes a very important limitation for model calibration and scenario analysis, due to the large number of model runs generally required. This paper presents a framework for ecological simulations that intends to increase system performance through the ability to do parallel simulations, allowing the joint analysis of different scenarios. This framework evolved from the usage of one simulator and several agents, that configure the simulator to run specific scenarios, related to possible ecosystem management options, one at a time, to the use of several simulators, each one simulating a different scenario concurrently, speeding up the process and reducing the time for decision between the alternative scenarios proposed by the agents. This approach was tested with a farmer agent that seeks optimal combinations of bivalve seeding areas in a large mariculture region, maximizing the production without exceeding the total allowed seeding area. Results obtained showed that the time needed to acquire a "near" optimal solution decreases proportionally with the number of simulators in the network, improving the performance of the agent's optimization process, without compromising its rationality. This work is a step forward towards an agent based decision support system to optimize complex environmental problems.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7