Learning type-generalized skills for symbolic planning for autonomous devices

A computer-implemented method for learning operators for planning a behavior of an autonomous device, the method comprising:

• obtaining a set of training data including observations on a plurality of skills executable by the autonomous device in an interaction with at least one entity for addressing a first task;
• obtaining a set of predetermined data defining a hierarchy of entities including the at least one entity;
• learning a set of individual skills based on the obtained set of training data;
• generating an enhanced set of skills by generalizing the individual skills of the learned set of individual skills based on the predetermined set of data that defines the hierarchy of entities and adding the generalized individual skills to the set of individual skills, and
• repetitively performing the step of generating the enhanced set of skills by generalizing the individual skills of the learned set of individual skills based on the predetermined set of data until a convergence criterion is met;
• determining that the convergence criterion is met when, in the step of generalizing the individual skills of the learned set of individual skills, no new generalized skill can be found;
• and
• performing behavior planning of the autonomous device for addressing a second task different from the first task based on the enhanced set of skills.