Knowledge acquisition of strategy and tactics using fuzzy neural networks

A knowledge acquisition method using fuzzy neural networks (FNNs) is presented. The FNNs automatically acquire control strategy and tactics from the operator´s manipulating data. The acquired strategy and tactics coincide well with the operator´s image of strategic and tactical aspects of his controls. Steering of a ship with large inertia for passing through multiple gates is simulated. The FNNs extract the strategic and tactical rules from the operator´s steering data. A hierarchical controller, using the FNN with strategy for generating track commands and the FNN with tactics for steering the ship to follow the commands, is developed. The hierarchical controller exhibits good performance in steering the ship. The ship is able to pass through even untrained gate patterns