Design and Authorship for the Halberd Narrative Planning Engine

In interactive narratives, there is a trade-off between authorial control and player agency. To address this issue, our team developed Halberd, a game engine which uses planning techniques to produce branching narratives while keeping author workload manageable. Rather than writing story paths, the author writes a world, a set of characters, and an end goal, and the engine dynamically generates the story path based on player actions. Additionally, the engine handles procedural creation of scenes using individual art or text components. To evaluate the engine, we created and playtested a horror game, titled The Worm of Everhill. This report describes the design of the Halberd system, and discusses techniques of authorship for narrative planning engines

Automatic Game World Generation for Platformer Games Using Genetic Algorithm

Most of the games rely on the game designer to design the level and environment. Increasing of game environment space scale followed by increasing of time and cost. Procedural Content Generation (PCG) is a method to solve this problem by generating a game environment space. In this paper, a PCG method proposed using a genetic algorithm approach to solve the problem in generating game environment. Transition graph adapted in the proposed method to make PCG generate difficulty level. The Index-based approach used to display the biome sequence. This approach displays the biome according to its index in the sequence

Ludotopia

Where do computer games »happen«? The articles collected in this pioneering volume explore the categories of »space«, »place« and »territory« featuring in most general theories of space to lay the groundwork for the study of spatiality in games. Shifting the focus away from earlier debates on, e.g., the narrative nature of games, this collection proposes, instead, that thorough attention be given to the tension between experienced spaces and narrated places as well as to the mapping of both of these

A holistic approach for semantic-based game generation

The Web contains vast sources of content that could be reused to reduce the development time and effort to create games. However, most Web content is unstructured and lacks meaning for machines to be able to process and infer new knowledge. The Web of Data is a term used to describe a trend for publishing and interlinking previously disconnected datasets on the Web in order to make them more valuable and useful as a whole. In this paper, we describe an innovative approach that exploits Semantic Web technologies to automatically generate games by reusing Web content. Existing work on automatic game content generation through algorithmic means focuses primarily on a set of parameters within constrained game design spaces such as terrains or game levels, but does not harness the potential of already existing content on the Web for game generation. We instead propose a holistic and more generally-applicable game generation solution that would identify suitable Web information sources and enrich game content with semantic meta-structures.The research work disclosed in this publication is partially funded by the REACH HIGH Scholars Programme — Post- Doctoral Grants. The grant is part-financed by the European Union, Operational Programme II — Cohesion Policy 2014- 2020 Investing in human capital to create more opportunities and promote the wellbeing of society — European Social Fund.peer-reviewe

Procedural Content Generation: Goals, Challenges and Actionable Steps

This chapter discusses the challenges and opportunities of procedural content generation (PCG) in games. It starts with defining three grand goals of PCG, namely multi-level multicontent PCG, PCG-based game design and generating complete games. The way these goals are defined, they are not feasible with current technology. Therefore we identify nine challenges for PCG research. Work towards meeting these challenges is likely to take us closer to realising the three grand goals. In order to help researchers get started, we also identify five actionable steps, which PCG researchers could get started working on immediately