Towards an Ontology for Robot Introspection and Metacognition

Abstract

We present the Meta-Ontology for Introspection (MOI): Inspired by fundamental processes of the human mind, cognitive architectures (CAs) explore ever more methods to leverage metacognition. Still, an ontological model to trace metacognitive experiences for learning or as input for metacognitive control routines has yet to be developed. Based on a review of existing standards, we formally identify the relevant scope in the form of Competency Questions (CQs) and extend SOMA, a well-established formal ontology initially designed to interpret episodic memories of a robotic CA. The resulting MOI can model a CA’s software and capabilities of single components, trace information processing and inter-component communication, label self-lived mental events, and capture causal relationships. We evaluate MOI via the CQs and exemplarily demonstrate its reasoning capabilities.