Authors:
Ander Pijoan Lamas, Oihane Kamara Esteban, Cruz Enrique Borges Hernández, Yoseba K. Penya Landaburu

Abstract:

We present here an agent-based system tightly coupled to geographic information systems (GIS). Our objective is to simulate the growth of a city in order to foresee the evolution of the electrical demand in a given zone. The agents are deployed over a GIS-based Multi-Agent System platform where the geographical components have been abstracted from the agent system to the environment. The configuration model uses geographical information to improve the agents' connection and perception of the surrounding environment and based on their choices, we forecast urban evolution and derive the expected increment in electric consumption. We have validated our approach with real data and discuss here our conclusions.



Proceedings: Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems
Presented at:

AAMAS 2014 (2014)


ISBN:

978-1-4503-2738-1


Year:

2014


Pages:

12


Citation
Ander Pijoan Lamas, Oihane Kamara Esteban, Cruz Enrique Borges Hernández, Yoseba K. Penya Landaburu. (2014) "GIS and MAS tight coupling for Spatial Load Forecasting" In Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems. p. 12.