OntoPret: An Ontology for the Interpretation of Human Behavior

TL;DR

OntoPret is a formal ontology designed to enable machines to interpret complex human behaviors in real-time, supporting applications in manufacturing and gaming through reasoning about intentions and actions.

Contribution

This paper introduces OntoPret, a novel, modular ontology grounded in cognitive science for real-time interpretation of human behaviors in human-machine teaming.

Findings

Successfully applied in manufacturing and gameplay scenarios

Provides a formal framework for classifying behaviors including deviations and deception

Enables advanced reasoning about human intentions

Abstract

As human machine teaming becomes central to paradigms like Industry 5.0, a critical need arises for machines to safely and effectively interpret complex human behaviors. A research gap currently exists between techno centric robotic frameworks, which often lack nuanced models of human behavior, and descriptive behavioral ontologies, which are not designed for real time, collaborative interpretation. This paper addresses this gap by presenting OntoPret, an ontology for the interpretation of human behavior. Grounded in cognitive science and a modular engineering methodology, OntoPret provides a formal, machine processable framework for classifying behaviors, including task deviations and deceptive actions. We demonstrate its adaptability across two distinct use cases manufacturing and gameplay and establish the semantic foundations necessary for advanced reasoning about human intentions.