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In many real world problems, optimisation decisions have to be made with limited information. The decision maker may have no a priori or posteriori data about the often nonconvex objective function except from on a limited number of data points. The scarcity of data may be due to high cost of observation or fast-changing nature of the underlying system. This paper presents a "black-box" optimisation framework that takes into account the information collection, estimation, and optimisationdoi:10.4108/icst.valuetools.2011.245775 dblp:conf/valuetools/Alpcan11 fatcat:gqhebxcbcnfnzdeqpazimbzfaa