This paper addresses the procedural generation of levels for collaborative puzzle-platform games. To address this issue, we distinguish types of multiplayer interaction, focusing on two-player collaboration, and identify relevant game mechanics for a puzzle-platform game, addressing player movement, interaction with moving game objects, and physical interaction involving both players. These are further formalized as game design patterns. To test the feasibility of the approach, a level generator has been implemented based on a rule-based approach, using the existing tool called Ludoscope and a prototype game developed in the Unity game engine. The level generation procedure results in over 3.7 million possible playable level variations that can be generated automatically. Each of these levels encourages or even requires both players to engage in collaborative gameplay.
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A level designer typically creates the levels of a game to cater for a certain set of objectives, or mission. But in procedural content generation, it is common to treat the creation of missions and the generation of levels as two separate concerns. This often leads to generic levels that allow for various missions. However, this also creates a generic impression for the player, because the potential for synergy between the objectives and the level is not utilised. Following up on the mission-space generation concept, as described by Dormans, we explore the possibilities of procedurally generating a level from a designer-made mission. We use a generative grammar to transform a mission into a level in a mixed-initiative design setting. We provide two case studies, dungeon levels for a rogue-like game, and platformer levels for a metroidvania game. The generators differ in the way they use the mission to generate the space, but are created with the same tool for content generation based on model transformations. We discuss the differences between the two generation processes and compare it with a parameterized approach.
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ConceptThe goal of the worksop/tutorial is to introduce participants to the fundamentals of Procedural Content Generation (PCG) based on generative grammars, have them experience an example of such a system first-hand, and discuss the potential of this approach for various areas of procedural content generation for games. The principles and examples are based on Ludoscope, a software tool developed at the HvA by Dr. Joris Dormans, e.a.Duration: 2 hoursOverviewWe will use the first 30 minutes to explain the basics of how to use generative grammars to generate levels. The principles of these grammars and model transformations will be demonstrated by means of the level generation system of Spelunky, which we have modeled in Ludoscope.Spelunky focuses solely on the generation of geometry, but grammar-based systems can also be used to transform more abstract concepts of level design into level geometry. In the next hour, the participants will be able to get some hands-on experience with Ludoscope. The assignment will be to generate a Mario-like level based on specific requirements, adapted to the interests of workshop participants.Finally, we are interested in the participants’ evaluation of this approach to PCG. We will use the last 20 minutes to discuss alternative techniques, and possible applications to other areas of PCG, like asset creation, scripting and game generation.Workshop participants are asked to bring a (PC) laptop to work on during the workshop, and are encouraged to work in pairs.
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Grammar-based procedural level generation raises the productivity of level designers for games such as dungeon crawl and platform games. However, the improved productivity comes at cost of level quality assurance. Authoring, improving and maintaining grammars is difficult because it is hard to predict how each grammar rule impacts the overall level quality, and tool support is lacking. We propose a novel metric called Metric of Added Detail (MAD) that indicates if a rule adds or removes detail with respect to its phase in the transformation pipeline, and Specification Analysis Reporting (SAnR) for expressing level properties and analyzing how qualities evolve in level generation histories. We demonstrate MAD and SAnR using a prototype of a level generator called Ludoscope Lite. Our preliminary results show that problematic rules tend to break SAnR properties and that MAD intuitively raises flags. MAD and SAnR augment existing approaches, and can ultimately help designers make better levels and level generators.
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This paper discusses the potential application of procedural content generation to a game about economical crises, intended to teach a large general audience about how banks function within a market-guided economy, and the financial risks and moral dilemmas that are involved. Procedurally generating content for abstract and complex notions such as inflation, market crashes, and market flux is different from generating spatial maps or physical assets in a game, and poses several design challenges. Instead of generating these kinds of phenomena and other macro-economic effects directly, the designers aim to let them emerge from automatically generated game mechanics. The game mechanics we propose include generic business models that can be parameterized to model the behavior of companies in the game, while the player controls the actions of a bank. What makes generating these game mechanics particularly challenging is the interaction between phenomena at different levels of abstraction. Therefore, relevant economic concepts are discussed in terms of design challenges, and how they could be modeled as emergent properties using generative methods.
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Pain following burn injuries can be severe and may persist after hospital discharge. The experience of pain is influenced by multiple biological and psychosocial factors. Post-discharge pain may be related to pain experienced during hospitalization as well as anxiety associated with these pain experiences. There are also protective factors; one notable example is optimism. However, the role of optimism in burn-related pain has not yet been investigated. This study aimed to describe the extent of pain measured over 14 consecutive days post-discharge and to examine its relationship with background pain, procedural pain, pain-related anxiety, and optimism. This multi-center longitudinal cohort study was conducted in five burns centres. The results showed that 50 % of the patients had a pain score ≥ 2 on a 0 – 10 scale after discharge, which on average decreased further over the next 14 days. However, a subgroup of patients maintained elevated pain levels. Patients with higher pain scores post-discharge were more likely to have experienced higher levels of background pain and procedural pain in-hospital and they scored lower on optimism. Pain-related anxiety did not independently contribute to pain post-discharge. The results indicate that patients with high pain scores during hospital admission may need specific attention regarding pain management when they leave the hospital. Furthermore, patients may benefit from optimism-inducing interventions in the hospital and thereafter.
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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.
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Het RAAK MKB-project Geautomatiseerd Game Design is na de oorspronkelijke projectduur van 1 maart 2013 t/m 31 mei 2015 nog met drie maanden uitgebreid om nog gebruik te kunnen maken van tot dan toe onbenutte projectresources, ten behoeve van (1) de ontwikkeling van cursus- en trainingsmateriaal, (2) evaluatie van dit cursus- en trainingsmateriaal, en (3), verfijning, verduurzaming, en disseminatie van de resultaten van het project. Dit rapport geeft een verslag van de activiteiten en resultaten van deze extensieperiode, van 1 oktober t/m 31 december 2015.Projectnummer 2012-20-43M, Subsidieperiode : 1 maart 2013–31 mei 2015 + extensie van 1 okt-31 dec 2015
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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.
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This paper starts with the explanation of the research rationale of the professorship. Subsequently, an exploration of the research agenda is provided, focusing on the two core research themes of the professorship: transformational content strategy and transformational content design. Within this section, knowledge gaps will be identified and examples will be presented of research projects related to each theme. Finally, light will be shed on the research approach, offering a brief overview of the theoretical approach, research methodology, and expected impact.
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