1. An object investigation and classification system comprising: an object test system that receives a command to perform at least one action with a test object, performs the at least one action with the test object, and returns test information indicative of at least one percept resulting from the at least one action; a data storage system that contains an experience database containing data indicative of multiple classifications and, for each classification, at least one action that was performed with at least one previously-observed reference object having this classification, and at least one percept value that is based in whole or in part on the test information resulting from the at least one action; and a data processing system that: a) for each of multiple different classifications, computes or receives an initial prior probability that a test object falls within the classification; b) determines at least one action that should be performed with the test object to obtain at least one percept about the test object that is likely to enable the classification of the test object to be more accurately determined based on the initial prior probabilities and the data within the experience database; c) causes the object test system to perform the at least one action with the test object; d) receives test information from the object test system indicative of at least one percept resulting from the at least one action with the test object; e) computes at least one percept value; f) for each of multiple different classifications, determines a posterior probability that the test object falls within the classification based on the initial prior probability, the at least one percept value, and data within the experience database; g) determines whether any of the posterior probabilities meets or exceeds a threshold; h) if none of the posterior probabilities meet or exceed the threshold, repeats b) through i), substituting the posterior probabilities determined in f) for the initial prior probabilities in b); and i) when one or more of the posterior probabilities meets or exceeds the threshold, outputs information indicative of one or more of the classifications that correspond to the one or more posterior probabilities that meets or exceeds the threshold.