Using Theory Completion to Learn a Robot Navigation Control Program.

An Event Calculus program to control the navigation of a real robot was generated using Theory Completion techniques. This is an application of ILP in the non-observational predicate learning setting. This work utilized 1) extraction-case abduction; 2) the simultaneous completion of two, mutually related predicates; and 3) positive observations only learning. Given time-trace observations of a robot successfully navigating a model office and other background information, Theory Completion was used to induce navigation control programs in the event calculus. Such programs consisted of many clauses (up to 15) in two mutually related predicates. This application demonstrates that abduction and induction can be combined to effect nonobservational multi-predicate learning.