Executable Ontologies in Game Development: From Algorithmic Control to Semantic World Modeling

• URL: http://arxiv.org/abs/2601.07964v1
• Date: Mon, 12 Jan 2026 19:57:35 GMT
• Title: Executable Ontologies in Game Development: From Algorithmic Control to Semantic World Modeling
• Authors: Alexander Boldachev,
• Abstract summary: We argue that Executable Ontologies (EO) represent a transition from algorithmic behavior programming to semantic world modeling.<n>We show how EO achieves prioritybased task interruption through dataflow conditions rather than explicit preemption logic.
• Score: 51.56484100374058
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This paper examines the application of Executable Ontologies (EO), implemented through the boldsea framework, to game development. We argue that EO represents a paradigm shift: a transition from algorithmic behavior programming to semantic world modeling, where agent behavior emerges naturally from declarative domain rules rather than being explicitly coded. Using a survival game scenario (Winter Feast), we demonstrate how EO achieves prioritybased task interruption through dataflow conditions rather than explicit preemption logic. Comparison with Behavior Trees (BT) and Goal-Oriented Action Planning (GOAP) reveals that while these approaches model what agents should do, EO models when actions become possible - a fundamental difference that addresses the semantic-process gap in game AI architecture. We discuss integration strategies, debugging advantages inherent to temporal event graphs, and the potential for LLM-driven runtime model generation.

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