The Behavior Modeling of Battlefield Individual Based on Mate-agents

Considered actions of Virtual battlefield individual with the intelligence and autonomy characteristic, internal factors that influence personnel external behavior were broken down into mate-Agents with considering behavior functions, and a battlefield individual behavioral model was advanced by aggregating mate-Agents. Mate-Agent structure was accomplished by intelligent model based on its main features, with describing values and reliability of perception factors, using fuzzy wavelet algorithm for the decision-making data classification, achieving subjective composite indicator with the RBF neural network learning. Compared with traditional methods, the mate-Agents aggregation behavioral model greatly improves the intelligence, autonomy and diversity of behavior by handling the coupling and complex interactions of mate-Agents, which provide a new approach to battlefield individual action modeling.