AWGS-Core: A Dynamic Ontological Framework for Emergent World Simulation

AWGS-Core (Adaptive World Generation System Core) is an experimental computational framework designed for dynamic world simulation through ontological modeling, emergent systems, and hybrid semantic processing. The framework transforms natural language inputs into evolving simulated worlds composed of entities, relations, rules, memory states, and narrative outputs. Unlike traditional procedural generation systems that rely primarily on static rule sets or handcrafted pipelines, AWGS-Core explores process-oriented architectures where semantic structures evolve dynamically over time. The system combines symbolic representations, adaptive simulation logic, relational modeling, and hybrid AI-assisted semantic extraction while preserving operational continuity through deterministic fallback systems when external AI services are unavailable. The project was developed as an experimental research prototype with assistance from generative AI tools during parts of the writing, ideation, debugging, and structural refinement processes. However, the conceptual architecture, ontological design principles, simulation logic, and research direction are original contributions of the author. Potential applications include procedural generation, adaptive simulations, symbolic AI systems, game ecosystems, emergent narrative systems, and complex computational environments.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-17
DOI
https://doi.org/10.5281/zenodo.20260253
Primary Topic
Artificial Intelligence in Games
Type
article
Field-Weighted Citation Impact
0.00
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article

AWGS-Core: A Dynamic Ontological Framework for Emergent World Simulation

Luis Felipe Martinez Bastidas
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Games
article

AWGS-Core: A Dynamic Ontological Framework for Emergent World Simulation

Luis Felipe Martinez Bastidas
article en

Abstract

AWGS-Core (Adaptive World Generation System Core) is an experimental computational framework designed for dynamic world simulation through ontological modeling, emergent systems, and hybrid semantic processing. The framework transforms natural language inputs into evolving simulated worlds composed of entities, relations, rules, memory states, and narrative outputs. Unlike traditional procedural generation systems that rely primarily on static rule sets or handcrafted pipelines, AWGS-Core explores process-oriented architectures where semantic structures evolve dynamically over time. The system combines symbolic representations, adaptive simulation logic, relational modeling, and hybrid AI-assisted semantic extraction while preserving operational continuity through deterministic fallback systems when external AI services are unavailable. The project was developed as an experimental research prototype with assistance from generative AI tools during parts of the writing, ideation, debugging, and structural refinement processes. However, the conceptual architecture, ontological design principles, simulation logic, and research direction are original contributions of the author. Potential applications include procedural generation, adaptive simulations, symbolic AI systems, game ecosystems, emergent narrative systems, and complex computational environments.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 4%
Artificial Intelligence in Games
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AWGS-Core: A Dynamic Ontological Framework for Emergent World Simulation — Luis Felipe Martinez Bastidas · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS