1. A decision making mechanism of an active perception module of a robot, the active perception module including at least one processing unit executing one or more instructions from a non-transitory machine-readable medium, said decision making mechanism being operable to decide on at least one prospective action of a robot from a set of actions of said robot by: the active perception module computing a prior probabilistic representation of a prior environment state; the active perception module updating of said prior probabilistic representation with targets of a new observation following the at least one prospective action after an action period, the action period comprising a period for incorporating an action observation pair into an update of an environment state, thereby reducing at least one uncertainty in a posterior probabilistic representation of a posterior environment state to be reached after an appliance of said at least one prospective action, wherein said posterior probabilistic representation is a probabilistic representation resulting from said updating; the active perception module determining an information gain between said prior probabilistic representation and said posterior probabilistic representation by use of at least one information theoretic measure; and the active perception module evaluating said at least one prospective action by estimating the costs of executing said at least one prospective action during the action period and estimating said information gain at the end of the action period.
9. The decision making mechanism according to claim 1 , wherein said updating comprises an estimating of the new observation, which will be obtained after executing of said at least one prospective action.