The persistent rise in demand for content in the gaming industry means that programs with the ability to produce content autonomously will save an extraordinary amount of time and cost. In that context, this thesis proposes a novel architecture for procedural narrative generation and Implements it as software called Automatic Quest Planning Generator (AQPG). The architecture combines the computation of Event Segmentation Theory (EST) with Artificial Intelligence (AI) planning methods to automatically generate quests. The idea in this work is that since Event Segmentation generates actions and goals to facilitate planning in humans, a good representation of these types of events either in natural language text or other media should be able to automatically generate planning components for an AI planning system as well. Results from this work found that the AQPG system is capable of generating planning files that can be used for quest generation.