15. A computer-implemented method comprising: identifying a first partition of data with a fact category, a second partition of data with an information category, a third partition of data with a hypothesis category, and a fourth partition of data with a directive category; identifying a first partition of transformative actions with a classification category, a second partition of transformative actions with an assessment category, a third partition of transformative actions with a resolution category, and a fourth partition of transformative actions with an enactment category; invoking a first action to produce a second set of data from the information category; invoking a second action to produce a third set of data from the hypothesis category; invoking a third action to produce a fourth set of data from the directive category; invoking a fourth action to produce a fifth set of data from the fact category; invoking a classification action on a first set of facts to produce a first set of information; invoking an assessment action on the first set of information to produce a first set of hypotheses; invoking a resolution action on the first set of hypotheses to produce a first set of directives; invoking an enactment action on the first set of directives to modify system behavior and to produce a second set of facts that differs from the first set of facts; wherein invoking the classification action comprises applying a set of functions that maps a particular feature vector to an observation, a prediction, a norm, or an objective in the first set of information; and wherein the particular feature vector is a vector that includes a feature object.
15. A computer-implemented method comprising: identifying a first partition of data with a fact category, a second partition of data with an information category, a third partition of data with a hypothesis category, and a fourth partition of data with a directive category; identifying a first partition of transformative actions with a classification category, a second partition of transformative actions with an assessment category, a third partition of transformative actions with a resolution category, and a fourth partition of transformative actions with an enactment category; invoking a first action to produce a second set of data from the information category; invoking a second action to produce a third set of data from the hypothesis category; invoking a third action to produce a fourth set of data from the directive category; invoking a fourth action to produce a fifth set of data from the fact category; invoking a classification action on a first set of facts to produce a first set of information; invoking an assessment action on the first set of information to produce a first set of hypotheses; invoking a resolution action on the first set of hypotheses to produce a first set of directives; invoking an enactment action on the first set of directives to modify system behavior and to produce a second set of facts that differs from the first set of facts; wherein invoking the classification action comprises applying a set of functions that maps a particular feature vector to an observation, a prediction, a norm, or an objective in the first set of information; and wherein the particular feature vector is a vector that includes a feature object. 21. The system of claim 15 , the storage medium storing further instructions which, when executed by the one or more processors, cause the processors to perform operations comprising: matching a first profile vector for a particular actor to a second profile vector to select the particular actor from a plurality of actors to perform at least one of the classification action, the assessment action, the resolution action, or the enactment action; wherein the first profile vector is computed based at least in part on tacit knowledge, a social network, and specified preferences; wherein the second profile vector is computed based at least in part on functions that map classifications, assessments, resolutions, and enactments to the second profile vector.