International Journal on Science and Technology

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Development of Autonomous NPC Worker Agents through a Modular GOAP Architecture in 3D Simulations

Author(s) June Aurelius Bencila Jacinto, Mark Kevin Sanig, Sherillen Gavino Namuag, Prof. Edgardo Deloria Olmoguez II
Country Philippines
Abstract The study investigates the optimization of autonomous agent labor cycles within 3D interactive simulations, addressing the persistent boring manual NPC management. The study proposes a modular architecture for Goal-Oriented Action Planning (GOAP) specifically designed to handle and automate constant directives to worker-class entities. Developed in Unity 3D, the framework uses a dependency-layered planner that treats environmental events and prerequisites as dynamic variables. By evaluating both global world states and internal agent needs, the system enables NPCs to autonomously prioritize and sequence complex tasks from resource acquisition and structural construction to base defense. Unlike traditional Finite State Machine (FSM) models, this modular approach separates high-level goals from procedural actions, enabling task shifting and interruptions. The empirical evaluation results from fifteen respondents, using a five-point Likert scale, scored the system’s effectiveness with a functionality mean of 4.42, a reliability mean of 4.25, and an efficiency mean of 4.30, resulting in a cumulative weighted mean of 4.32. These findings confirm that integrating dependency-based logic into a modular GOAP framework enhances NPC agency and decision-making accuracy. The research provides a scalable technical blueprint for developers to implement self-sufficient autonomous agents, elevating the experience of 3D simulations while effectively reducing the cognitive load on players during complex simulation scenarios.
Keywords Goal-oriented Action Planning, Game Artificial Intelligence, Autonomous Agents, Non-player Characters, Unity 3d
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 17, Issue 1, January-March 2026
Published On 2026-03-28
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