Ontology of Tasks and Methods

TLDR

Ontologies in AI have largely focused on modeling reality—objects, relations, states, events, and processes—while also exploring domain‑independent problem‑solving methods, yet explicit links to domain ontologies remain underdeveloped. This paper aims to connect domain ontologies with the ontology of problem‑solving methods to enable shared, standardized representations of knowledge. The authors conduct a review and synthesis of prior work on task and method ontologies.

Abstract

Much of the work on ontologies in AI has focused on describing some aspect of reality: objects, relations, states of affairs, events, and processes in the world. A goal is to make knowledge sharable, by encoding domain knowledge using a standard vocabulary based on the ontology. A parallel attempt at identifying the ontology of problem-solving knowledge has a goal of sharable problem-solving methods. For example, when one is dealing with abductive inference problems, the following are some of the terms that occur in the representation of problem-solving methods: hypotheses, explanatory coverage, evidence, likelihood, plausibility, composite hypothesis, etc. Method ontology is, in good part, goal- and method-specific. ``Generic Tasks,'' ``Heuristic Classification,'' ``Task-specific Architectures,'' ``Task-method Structures,'' ``Inference Structures'' and ``Task Structures'' are representative bodies of work in the knowledge-systems area that have focused on domain-independent problem-solving methods. However, connections have not been made to work that is explicitly concerned with domain ontologies. Making such connections is the goal of this paper. This paper is part review and part synthesis.