This paper presents a control strategy that uses a hierarchical structure to arbitrate between recommendations from lower level modules. The lower level modules represent lower level tasks or behaviors. Each lower level module provides its own control recommendation based on its limited perception of the environment.

We introduce the concept of a fuzzy quality measure that may be used by the hierarchical controller to determine how best to fuse the individual recommendations. The Quality Measure provides an approximate determination of each control recommendations potential value.

The hierarchical partitioning reduces the cardinality of the rule base and decreases the number of system parameters, as compared to a monolithic structure. Optimization of the reduced parameter set is simpler and requires less time.

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