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The development of a new hierarchical linguistic-based learning control structure for complex systems is described. The complete system will be able to interact with a human operator in a high-level language at the highest level of the hierarchy and will be able to control detailed motions of a complex physical system at the lowest level of the hierarchy. Each level of the hierarchy is defined by a formal grammar which can generate exactly the class of admissible control actions at that level. A new linguistic structure, the linguistic decision schema, is proposed to specify the mapping between linguistic elements in adjacent levels. In the most general form, the decision schema incorporates a learning algorithm to obtain asymptotically optimal mappings for control under stochastic environments.