This paper investigates strategies to generate levels for action-adventure games. For this genre, level design is more critical than for rule-driven genres such as simulation or rogue-like role-playing games, for which procedural level generation has been successful in the past. The approach outlined by this article distinguishes between missions and spaces as two separate structures that need to be generated in two individual steps. It discusses the merits of different types of generative grammars for each individual step in the process. Notably, the approach acknowledges that the online generation of levels needs to be tailored strictly to the actual experience of a player. Therefore, the approach incorporates techniques to establish and exploit player models in actual play.
Within the context of the Iliad project, the authors present technical challenges and the first results of having valid 3D scenes of (non-)existing offshore wind farms procedurally and automatically generated within either the Unreal or Unity game engine. The Iliad – Digital Twins of the Ocean project (EU Horizon 2020) aims to develop a ‘system of systems’ for creating cutting-edge digital twins of specific sea and ocean areas for diverse purposes related to their sustainable use and protection. One of the Iliad pilots addresses the topic of offshore floating wind farm construction or maintenance scenario testing and validation using the Unity 3D game engine. This work will speed up the development of these scenarios by procedurally and automatically creating the Unity 3D scene rather than manually (which is done at present). The main technical challenges concern the data-driven approach, in which a JSON configuration file drives the scene creation. The first results show a base wind farm running in Unreal 5.1. The final product will be able to handle environmental conditions, biological conditions, and specific human activities as input parameters.
PCK is seen as the transformation of content knowledge and pedagogical knowledge into a different type of knowledge that is used to develop and carry out teaching strategies. To gain more insight into the extent to which PCK is content specific, the PCK about more topics or concepts should be compared. However, researchers have rarely compared teachers’ concrete PCK about more than one topic. To examine the content dependency of PCK, we captured the PCK of sixteen experienced Dutch history teachers about two historical contexts (i.e. topics) using interviews and Content Representation questionnaires. Analysis reveals that all history teachers’ PCK about the two contexts overlaps, although the degree of overlap differs. Teachers with relatively more overlap are driven by their overarching subject related goals and less by the historical context they teach. We discuss the significance of these outcomes for the role of teaching orientation as a part of PCK.
The Hereon team has expressed interest in the use of the PO platform for the virtualization of the (hydro)dynamic behavior of offshore wind farms, in particular regarding turbidity around wind turbines. BUas has developed the Procedural Ocean (PO) platform. The platform uses procedural content generation (AI) for data-driven 3D virtualization of complex marine and maritime environments, with elements such as geo-environment (bathymery, etc.), geo-physics (weather conditions, waves), wind farms, aquaculture, shipping, ecology, and more. The virtual and immersive environment in the game engine Unreal supports advanced (game-like) user interaction for policy-oriented learning (marine spatial planning), ocean management, and decision making. We therefore propose a joint pilot Research and Development (R&D) project to explore, demonstrate and validate how a gridded dataset provided by Hereon can show the dynmics around wind farm monopiles. Furthermore, we can explore interactivity with the engineering and design of the turbine and the multiplication of the turbine design to compose a wind farm. Client: Hereon (The Helmholtz-Zentrum Hereon is a non-profit making research institute )
