Multi-agent Behavior Evolutionary Analysis on Building Energy Efficiency Economic Incentive System in China Based on Cellular Automata

Building energy efficiency (BEE) economic incentive system is an enormous system of multi-agent, which includes government departments, design institutes, construction units, real estate development enterprises, purchasers and energy service companies etc. It has a widely internal relationship and a character of multi-layer, multi-function, dynamic, open and mutually learning, so it is conformed that this system has the basic character of complex system. As a rational method to solve the problem of complex system, cellular automata (CA) can analyze the grid dynamic model which is not only discrete in temporal and spatial aspects but also partial in temporal consequence and spatial mutual relationship. Under some certain simple units and regulations, CA can simulate the complex system veritably. With the bottom-up modeling method of CA, this study establishes an evolutionary model of multi-agent for BEE economic incentive system in China through analyzing the complex character of this system. Based on the analytic result of evolving processes, it is recognized that the influence factors of promoting BEE economic incentive policy involves behavior preference, macro environment factors and different actual conditions of local regions