Toward an Agent-Based Multi-scale Recommendation System for Brown Plant Hopper Control

Rice pest control problem is multi-disciplinary in scope and includes multi-scale processes. Brown plant hopper is one of the most destructive pests of rice, there are potential risks for rice production if population of this insect is high. In this paper, an agent-based multi-scale model is made of agent-based sub-models in different studies, this model works as a Brown plant hopper recommendation system and supports experts to simulate Brown plant hopper control strategies. This recommendation system includes sub-models that have different functions: growth and invasion models of Brown plant hopper, upscaling and downscaling information models. Simulation results of Brown plant hopper management strategies help stakeholders assess Brown plant hopper infestation status of rice areas and make recommendation messages to farmers.