Abstract
A novel method of hierarchical parallel search is proposed for dealing with Markov planning/control processes in systems with uncertain information. It is based on a new concept of analyzing alternatives with uncertain cost evaluation. Under definite conditions, instead of making immediate choices based on the expectation of cost at each step of the search, it is recommended to postpone the final decision until information is improved and the uncertainty is reduced. In addition to elementary alternatives their combinations are also considered for possible pursuit. >
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