ROSS User's Guide and Reference Manual (Version 1.0)
It addresses representation and reasoning challenges in AI and natural language understanding, but appears incremental as it builds on existing symbolic and ontological frameworks.
The paper introduces the ROSS method, a new knowledge representation approach for AI and natural language tasks, which provides a declarative model for physical structure, processes, and causality based on a 4D metaphysical view.
The ROSS method is a new approach in the area of knowledge representation that is useful for many artificial intelligence and natural language understanding representation and reasoning tasks. (ROSS stands for "Representation", "Ontology", "Structure", "Star" language). ROSS is a physical symbol-based representational scheme. ROSS provides a complex model for the declarative representation of physical structure and for the representation of processes and causality. From the metaphysical perspective, the ROSS view of external reality involves a 4D model, wherein discrete single-time-point unit-sized locations with states are the basis for all objects, processes and aspects that can be modeled. ROSS includes a language called "Star" for the specification of ontology classes. The ROSS method also includes a formal scheme called the "instance model". Instance models are used in the area of natural language meaning representation to represent situations. This document is an in-depth specification of the ROSS method.