Academic research has produced numerous innovative PCG techniques, yet procedural level design remains unevenly adopted across the game development community. To understand why, we conducted a comprehensive survey of 120 game development professionals examining what developers actually experience when working with procedural tools. The survey covered current tool usage, adoption barriers, technical preferences, and future needs across level designers, game designers, technical artists, environment artists, programmers, and researchers. We present and analyze the survey responses using various techniques and visualizations. In addition, we developed an interactive online tool for anyone to explore patterns across demographic data segments and draw their own interpretations.

Artificial intelligence (AI) is rapidly reshaping daily life, yet its environmental costs such as electricity use, cooling water consumption and electronic waste, remain largely invisible to the public. This lack of awareness persists due to both limited corporate transparency and insufficient media attention. To address this gap, we present Outsourced, a virtual reality (VR) serious game designed to raise awareness on AI’s environmental impact. The gameplay combines VR immersion with a dual-perspective narrative, alternating between home and workplace settings, and illustrating how both individual AI use and corporate practices jointly contribute to ecological degradation. Preliminary evaluation of the game shows that Outsourced effectively conveyed the severity of electricity, water, and e-waste involved in AI infrastructure, though participants struggled to connect their personal AI habits to these resource demands. Our work contributes a novel, immersive approach to environmental education, demonstrating how a VR serious game can make abstract ecological issues tangible and personally meaningful.

Frontotemporal dementia (FTD) is the second most common cause of young-onset dementia and is typically caused by frontal and/or temporal lobe degeneration [1]. This degeneration impacts personality, judgment, and the ability to recognize emotion. Early diagnosis of FTD is critical for effective treatment, but current diagnostic tools often lack the realism necessary to assess social cognitive abilities like emotion recognition and theory of mind. We propose the customization of an immersive virtual reality (VR) experience to improve early FTD diagnosis by creating realistic social interactions in immersive environments. Our approach is two-fold: (i) an authoring tool that gives neuropsychologists generative AI support for writing a suitable dialog involving faux pas, picking characters and voicing them; (ii) a VR game in which patients observe the enactment of those scripted social scenarios, guided by a virtual companion. We discuss the main features of our current prototype, and identify some development and evaluation challenges ahead.

Procedural Content Generation methods enable the creation of varied content algorithmically. One such method is Wave Function Collapse (WFC), a tile-based local constraint solver commonly applied to texture, map and level generation for grid-based content; it is able to create varied output from the same set of rules, usually derived from an input sample. However, a glaring limitation of WFC is that it only operates on tiles of the same shape and size. We propose Non-Uniform Tile Wave Function Collapse (nutWFC), an extension of WFC that supports multi-cellular tiles with varying shapes and sizes, so-called Non-Uniform Tiles (NUTs). Familiar examples of such tiles can be found in LEGO ® and Tetris. The algorithm guarantees NUT shape and size preservation even under WFC's Overlapping Model in three dimensions. We show that nutWFC is a super-set of WFC that harmonizes strict NUT shape and size constraints with WFC's output diversity without significant performance penalties. We illustrate the expressive power of nutWFC with a few results that explore the advantages of NUTs and would therefore not be feasible with WFC.

Learning motor skills is essential to many different aspects of life, from big movements needed for sports to small and simple movements used in the rehabilitation of stroke patients. In recent years, sonification, i.e. using sounds as feedback for actions, has been researched as a promising technique for studying motor behavior. In particular, we explore how to use sonification to make the process of learning motor skills accessible and engaging. We posit that an interactive and gamified environment can increase the engagement in that process. Moreover, an enjoyable setting is more likely to stimulate repetition, an indispensable feature of any learning endeavor. We, therefore, designed and developed Pizzicato, a rhythm-based serious game that leads players to move their arms and hands to actively play music. The game uses a common webcam to track your hand movements: pinching one finger to the thumb at the right position and moment will play musical notes that pleasantly add up to a full musical track. Our player tests have shown that players find Pizzicato accessible and engaging, and report that playing the game gives them a strong sense of agency. Pizzicato was developed in collaboration with neuropsychology colleagues, who are now starting to use it as a flexible tool for motor behavior research, both for diagnostic and rehabilitation purposes.

Procedural Content Generation (PCG) has long been proposed as an answer to the increased workload imposed on designers of virtual worlds, although often at the cost of controllability and expression of designer intent. Mixed-initiative approaches promise to overcome this, and valid proposals have been made of mixed-initiative editors, e.g. driven by the Wave Function Collapse (WFC) algorithm [12]. However, stock WFC operates on a simple tileset without any hierarchy or semantic clustering, preventing designers from fluently expressing level of detail, leaving the constraint solving burden partly on them instead of on the algorithm. Hierarchical Semantic Wave Function Collapse (HSWFC) claims to solve this problem by hierarchically structuring its tileset of semantic tiles, featuring meta-tiles that can undergo intermediate collapses [2]. Employing an HSWFC interactive editor offering such features may significantly reduce cognitive load and, thus, make such an editor more appealing for widespread use. We describe a user study to test this hypothesis, by comparing and discussing the cognitive load assessed on designers using either a stock WFC-driven editor or an HSWFC-driven editor. Our findings confirm that there is a significant reduction in cognitive load when the HSWFC editor is employed in comparison to the stock WFC editor.

The science of collecting and analyzing vast amounts of data to make predictions or derive other types of conclusions is often called Big Data. It is expected that a new generation of college students will be studying and working with Big Data. However, at the secondary school level, a serious lack of knowledge about it has often been detected. We designed a serious game to introduce students to this topic. Because Big Data is far too complex to teach in a single game, we focused our game design on two main elements: data collection and data analysis. The game raises awareness on these topics by immersing players in realistic situations, in which they strategically place data collection centers and use the collected data to answer various appealing queries and scenarios. These scenarios exemplify several opportunities and risks of real-world uses of Big Data. From a preliminary evaluation of the game, we conclude that the current game design leads to a statistically significant increase in awareness.

There are few proposals to improve the interactivity and control of wave function collapse (WFC) in a mixed-initiative setting. Moreover, most WFC algorithm variants operate on an simple, unstructured set of tiles. This limitation on the level of control provided to designers hampers their creative work in various ways. We propose Hierarchical Semantic WFC, a generalized approach to WFC that organizes its tile-set into a hierarchy akin to a taxonomy induced by the relation ‘consists-of’. In such a hierarchical structure, abstract tiles (i.e. non-leaf nodes) can represent the first sketchy intentions of a designer (e.g. forest, urban, desert,...) This allows a designer to interactively collapse a given area into abstract tiles, while subsequently, (and repeatedly, if desired) WFC can resolve each area into a variety of particular instances, by further collapsing it into (a valid combination of) its children tiles (whether leaves or not). We identify how this subtle tile-set change affects the whole WFC algorithm, describe a number of novel exploratory and interactive functions that this enables, and showcase these with a variety of examples generated with our prototype implementation. We conclude that these new mixed-initiative content generation methods can considerably reduce design iteration times and improve the assistance given to designers in expressing their creative intent.

Conventional gait rehabilitation methods have the risk of alienating the patient due to their monotonous nature, thus negatively impacting the effectiveness of gait training. Modern technologies can help provide patients with better support, safety and immersive experience during training. However, physiotherapists cannot be required to master those technologies, nor to spend much time designing a more varied and engaging treatment for each patient. In this paper, we argue that adaptive gamified gait rehabilitation based on procedural content generation (PCG) can effectively support physiotherapists in achieving such customized outcomes. We propose a generic adaptation scheme to steer the generation of movement challenge levels based on player modeling and therapists’ intervention. Our approach features two difficulty adjustment strategies: parameter progression schemes and integration of multiple therapy goals. These strategies are applicable to the personalization of a wide range of gait rehabilitation goals. We implemented this approach in a standalone prototype for supporting gait training with the RYSEN system, a three-dimensional overground body weight support system. From our assessment with physiotherapists, we conclude that our PCG-based adaptive method effectively assists therapists in (i) offering a broad diversity in gait exercises to a wide group of patients, and (ii) dynamically tailoring challenge levels for a variety of gait tasks.

A narrative world typically consists of several interrelated locations that, all together, fully support enacting a given story. For this, each location in a narrative world features all the objects as required there by the narrative, as well as a variety of other objects that plausibly describe or decorate the location. Procedural generation of narrative worlds poses many challenges, including that, First, it cannot lean only on domain knowledge (e.g., patterns of objects commonly found in typical locations), and, second, it involves a temporal dimension, which introduces dynamic fluctuations of objects between locations. In this article, we present a novel approach for the procedural generation of narrative worlds, following two stages: first, anarrative world moldis generated (only once) for a given story; second, the narrative world mold is used to create one (or more) possible narrative worlds for that story. For each story, its narrative world mold integrates spatio-temporal descriptions of its locations with the object semantics and the domain knowledge previously acquired on typical locations. We describe how a narrative world mold can be generated, as well as how it can be fed to existing procedural generation methods, to create a variety of narrative worlds that fit that narrative. We evaluate our own implementation of this approach, performing a number of experiments that illustrate both the expressive power of narrative world molds and their ability to steer the generation of narrative worlds.

In recent years, the use of Augmented and Virtual Reality (ARNR) has taken a larger role within training and education of various fields, but not every individual experiences the benefits that AR and VR technology are thought to provide. The perspective taking skill of an individual may be a good indicator of the effectiveness that AR and VR training can achieve. However, we found that the tests in other research targeting small scale perspective taking are few and limited, as perspective taking is often hard to distinguish from mental rotation. Therefore, we designed and developed A Hole New Perspective, a serious game created specifically to test and train an individual’s perspective-taking ability. A Hole New Perspective focuses on the relationship between a 3D object floating in the air and a 2D hole on a moving wall. The core game mechanics consists of having the player rotate the object so that it fits in the hole, before the wall hits the object. Because players do not always have an aligned view with the hole, they have to call on their spatial perspective-taking abilities, in addition to mental rotation. We tested the game with a variety of test subjects, and compared these test results with the Perspective Taking/Spatial orientation Test. Early results have shown that performance in the game corresponds to mental rotation ability. Furthermore, there are indications that improvement in spatial ability through the game is selectively present for those with lower spatial abilities. This further substantiates the need for a more individualized approach when offering AR and VR in education. Additional training may be needed for some, but not all students.

Many people think of reforestation projects as one-dimensional, simply consisting of planting trees. In reality, a reforestation project takes into account a wide variety of factors, of which the three most important are improving soil quality, reducing fire hazard, and ensuring the prosperity of the community. We posit that a simplistic view on such projects is detrimental for a more committed and serious societal awareness and support of sustainable reforestation. Therefore, it is desirable that more people have a better understanding of the interplay of these factors, as they will likely become more involved in reforestation projects. We present Benni’s Forest, a serious game aimed at increasing awareness of the challenges of reforestation projects. Benni’s Forest is a simulation game, in which the player is responsible for a reforestation project, balancing its various factors over the years, deciding on what to do when and where on the terrain, e.g. fertilizing, planting trees, or digging fire ditches. Meanwhile, adverse events, like wildfires or illegal logging, threaten your progress, creating a tension that gives the player a vivid experience of the complexity of the project. As you progress, several scores indicate the quality of your performance, most notably a biodiversity score, representing the amount and variety of trees in the forest. In this way, players receive clear hints to strategize and face each situation with the appropriate measures to grow a biodiverse forest. We evaluated Benni’s Forest conducting a survey amongst players. The results confirm both an increased understanding of the challenges involved in reforestation efforts, and an increased sense of engagement of players with such projects.

Wave Function Collapse (WFC) is a powerful generative algorithm, able to create locally-similar output based on a single example input. One of the inherent limitations of the original WFC is that it often requires users to understand its inner workings, and possibly make their own ad-hoc mods, to achieve satisfactory results. Besides distracting from your creative task, this strongly reduces the algorithm’s effective usefulness to a small group of technical users. We propose miWFC, a novel mixed-initiative approach to WFC aimed at overcoming these drawbacks. Its main focus is on providing intuitive control to its users, in a way that matches their usual creative workflow. Among its main features, this approach provides (i) interactive navigation through design history, including controlled backtracking, (ii) precise manual editing of the output for direct expression of design intent, and (iii) interactive manipulation of tile weights, to tweak the global appearance of the output. We evaluated a prototype implementation of our approach among game artists and other creative professionals, and concluded that its features were largely considered useful and supportive of their creative work.

Most storytelling games bring people together to co-create stories. However, they often require considerable creative effort and skills from all players, possibly discouraging less resourceful participants and impairing stories’ quality. Moreover, most stories created within these games are usually only kept in players’ minds rather than on storage, despite being a valuable and original asset, with a large potential for the narrative research community. We address these challenges with a novel mixed-initiative approach aimed at supporting a group of players to incrementally co-create a story, one sentence at a time. Our method features a hand generator that offers a unique set of tokens (words) to each player in each turn. This generator carefully combines tokens relevant to the ongoing story, to each individual player, to the group as a whole and random. We implemented this method in TaleMaker, a multiplayer online game that stimulates playful co-creation of a story. TaleMaker gives players considerable creative freedom to compose their sentences, combining a gentle structural steering with the wisdom of the group to determine the best direction for the story. The collected output of TaleMaker consists of annotated stories, with slots (e.g. action, character, location) filled with words associated with a WordNet synset. From a preliminary evaluation, players reported that TaleMaker effectively stimulated story authoring, and perceived TaleMaker-created stories of considerable quality. In addition, a first analysis of the collected tokens confirms that players mostly collected story-related tokens, rather than those randomly offered.

Several datasets of stories and text have been proven useful for a variety of research fields. Yet, many of these datasets have suffered from the burden of being manually authored and/or annotated, affecting their size and potential to grow. To overcome this problem, we propose a novel database of stories collected from TaleMaker, an online multiplayer game that facilitates the playful co-creation of a story in order to eliminate the tedious task of authoring and annotating a dataset of stories. TaleMaker’s database relational schema provides a simple story representation, in which stories are named and clearly annotated. A story is composed of a sequence of plot points, each with several slots (e.g. action, character, location) filled with sense-annotated tokens (words) associated with a WordNet synset. In this paper, we describe in detail the database schema of TaleMaker’s stories repository. In addition, we suggest some of the potential applications of this repository of stories, including fostering research in fields such as story generation, narrative world generation, and word sense disambiguation.

Presently, one of the greatest challenges of humankind is climate change. It is usually assumed that its mitigation will require an extensive adaptation in many human habits. As every fourth ton of carbon dioxide emitted can be attributed to the food chain, it is argued that one of the most effective actions an individual can take is changing towards a more sustainable diet, like a plant-based one. Serious games have proved to be a successful means for achieving behavior change. We present Veganity, your journey, a mobile serious game aimed at assisting players in their transition towards a more plant-based diet. The game combines the characteristics of the idle game genre with diet tracking: in the game, as you progress in adapting your personal diet, you spare energy that can be spent in making the game world more sustainable. Personal factors, like changing your ecological or social norms, your habits and your behavioral costs and benefits, are targeted by different game mechanics. These include, among others, a currency mechanism for stimulating habit change, in-game actions building up self-efficacy, and tips raising problem awareness. Besides describing our game design, we also present the main features of the game implementation. From a preliminary evaluation, we conclude that Veganity, your journey successfully engages players in pursuing their own diet goals, and increases their reflection on, and acquaintance with, sustainable diet behaviors.

The papers in this special section focus on team artificial intelligence (AI) in games. Computer controlled players excel in a wide range of environments, from traditional board games, like chess and Go, to fast arcade environments like Super Mario Bros. and one versus one fighting. One of the topical issues of today’s research efforts aims at intelligent team behavior, relevant for a wide variety of games, including real-time strategy games, team sports, multiplayer online battle arena (MOBA), and even tabletop games like Hanabi. The notion of team behavior is very rich, ranging from the ability to exhibit a clear and consistent strategy of an AI-controlled team to the capability of “melting into” a group of human-controlled teammates and supporting their coordinated actions. Consequently, design goals of an AI system can be driven by a variety of considerations, including efficiency, creativity, believability, synergism, and contribution of the AI to the overall entertainment value of the game.

Procedural content generation (PCG) for architecture is widely used in a variety of digital media, most notably in games. However, such methods are often limited in their expressive range, and require considerable technical knowledge to create non-trivial architectural structures. We present a novel tile-based PCG approach for generating architecture, that proposes the use of architectural profiles, a declarative characterization of architectural typology, within a generic tile solving framework. An architectural profile consists of a set of tiles, representing atomic architectural building blocks, and a set of declarative constraints and rules, specifying which conditions a tile configuration has to satisfy to be valid. These conditions are translated into logic constraints, and used by a tile solver to control tile placement in a bottom-up manner. Eventually, each valid model output by the solver is a representative instance of its architectural profile. We describe an implementation of this approach with Answer Set Programming, using an off-the-shelf constraint solver for model generation. We performed an expressive range analysis, and concluded that our declarative method is quite controllable and can be steered over a broad range of architectural structures, regarding density and repetitiveness. Due to this expressive range and control, our tile-based method is very suitable for the customized development of urban environments for games.

Performance of newly-formed project teams is often limited, or at least delayed, when team members refrain from sharing their ideas due to unfamiliarity with their peers. A variety of ice-breaking methods can help overcome this cold start, but mostly they need to be deployed and moderated by experienced facilitators. This setup is rarely an option for most undergrad project courses at university level, typically carried out in small teams. In order to help breaking the ice in this context, we developed Maze Maestro, a collaborative tabletop game in which the board is made up by attaching the displays of the team members’ mobile phones to form a large maze. Each member controls a character in the maze, and the whole team has the common goal of leaving the maze together; however, this is only possible with timely communication and much cooperation. While playing, team members are encouraged to confer possible plans and share their ideas, which is the fertile ground for breaking the ice. Play testing has shown that Maze Maestro was perceived as a fun and original collaborative game. So far, results of a preliminary user study are optimistic about the ability of Maze Maestro to break the ice within newly-formed teams, without requiring any facilitator.

Procedural generation of rooms aims to create virtual environments that mimic common patterns found in real-world indoor locations, like offices or bedrooms. Graph-based models (e.g. factor graphs or Bayesian networks) have often been used to represent typical location's objects and their occurrence likelihood (nodes), as well as their inter-relationships (edges). Previous methods have struggled to represent object semantics in their graph nodes; specifically, they fail to fully and effectively support notions as abstractions (e.g. generic seat instead of chair) and replication (e.g. cups instead of cup). We propose a generalized representation and use for object semantics that overcomes the above limitations of graph-based models in the procedural generation of rooms. This node representation handles semantics as attributes, and clearly distinguishes the contribution of the attributes on the node from the potential effects of the node on the whole graph. We illustrate the additional expressive power of the resulting graph-based model for room generation, and show that it subsumes previous models as particular cases.

In recent years, many promising developments have taken place around augmented, virtual and mixed-reality technology. One could wonder whether these technologies can be combined to yield a mix of video games and sports, involving physical activities previously deemed impossible: creating a superhuman sport. This work investigates how mixed-reality can be used to create a fun, intuitive and engaging superhuman sport. To this end, the game League of Lasers was developed, in which two teams compete in a mix between football and Pong, using the physical movement of the players as main means to interact within mixed-reality. An evaluation of League of Lasers with a user study with 32 participants showed that League of Lasers is perceived as a fun and immersive skill-based game.

Superhuman sports (SHS) is a field where technological augmentations of human abilities and environment are combined to play a new and exciting sport. SHS make use of artificial senses or virtual reality to create a new experience that involves physical fitness and skills. Star Tag aims to combine these aspects with an engaging audience experience. This augmented reality game uses the Microsoft HoloLens, making it possible to move through a mixed reality space effectively. Star Tag is a competitive multiplayer game where players need to conquer all planets from their opponent to win the game. Players need to move around in a physical space from virtual planet to virtual planet in order to navigate the game-space and reach the planets. The audience is involved with the game via their phones, through which they can support the players. Through playtesting and conducting a survey, the results show that Star Tag is a superhuman sport that motivates people to be physically active.

—The design process is often characterized by and realized through the iterative steps of evaluation and refinement. When the process is based on a single creative domain such as visual art or audio production, designers primarily take inspiration from work within their domain and refine it based on their own intuitions or feedback from an audience of experts from within the same domain. What happens, however, when the creative process involves more than one creative domain such as in a digital game? How should the different domains influence each other so that the final outcome achieves a harmonized and fruitful communication across domains? How can a computational process orchestrate the various computational creators of the corresponding domains so that the final game has the desired functional and aesthetic characteristics? To address these questions, this paper identifies game facet orchestration as the central challenge for artificial-intelligence-based game generation, discusses its dimensions, and reviews research in automated game generation that has aimed to tackle it. In particular, we identify the different creative facets of games, propose how orchestration can be facilitated in a top-down or bottom-up fashion, review indicative preliminary examples of orchestration, and conclude by discussing the open questions and challenges ahead.

Non-Player Characters (NPCs) have actions that allow them to reason about what they can do in a game and how they can do it. The background information about what they can do are the components of the action, and how they can do it is the form or shape of an action, which may be built up from several sub-actions. The components and shape of an action must be fully defined in a game, which can be tedious when several similar actions are needed. Furthermore, as the number of nuanced actions grows, more pressure is placed on an already constrained reasoning system. By discovering the similarities between actions an NPC can do, a given action set can be intelligently organized with similar components being generalized using an action taxonomy. To understand the similarity between actions we have developed measures of action similarity based on their constituent components and form. From this, we discover a metric to determine the generalization ability of an organization strategy for an NPC action set. We examine the use of our measures on a previously developed action set to show the nuances between those actions. Lastly, we find that intelligently organizing actions has a positive effect on virtual character reasoning abilities.

• SBGames is the largest and most important scientific event for games and digital entertainment in Latin America. • It is attended by scientists, artists, designers, teachers and students from Colleges, Universities and the Game Industry. • It gathers around a thousand participants from different regions of Brazil and Countries as United States, England and Portugal. • SBGames is an In-Cooperation event of Eurographics and ACM SIGGRAPH and in 2018 it is held in the beautiful city of Foz do Iguaçu in a jointly conference.

Current research on adaptive games has mainly focused on adjusting difficulty in a variety of ways, for example, by providing some control over adaptive game world generation. These methods, however, are mostly ad-hoc and require quite some technical skills. To the best of our knowledge, so far, there has been no adaptive method that is truly generic and explicitly designed to actively include game designers in the content creation loop. In this paper, we introduce a generic method that enables designers to author adaptivity of game world generation, in a very expressive and specific fashion. Our approach uses adaptation rules, which build atop gameplay semantics in order to steer the online generation of the game content. Designers create these rules by associating skill profiles, describing skill proficiency, with content descriptions, detailing the desired properties of the specific game world content. This game content is then generated online using a matching and retrieval approach. We performed user studies with both designers and players and concluded that adaptation rules provide game designers with a rich expressive range to effectively convey specific adaptive gameplay experiences to players.

A road network is one of the core elements of urban environments, strongly defining their layout. Procedural modeling has been increasingly used to create such road networks. However, many procedural methods are complex and difficult to master by non-experts, often have a limited and hard-to-control expressive range, and require a variety of specialized input data to generate a complex road network. To mitigate this, some methods proposed to use stochastic data on road patches extracted from example maps to design a road network following a given urban style. We propose a novel patch-based method that uses the semantics of individual patches to help guiding the procedural generation. Our approach combines the advantages of patch-based generation with those of conventional parametric methods. Due to the intuitive character of semantic parameters and tags, our approach provides for an easy customization of fictive road network creation, allowing a user to easily define various types of road network styles, containing only the desired features and structures of real-world road networks.

Computers are often used as tools to design, implement, and even visualize a variety of narrative forms. Many researchers and artists are now further attempting to engage the computer actively throughout the development of the narrative itself. Any form of computational narrative authoring is at some level always mixed-initiative , meaning that the processing capabilities of the computer are utilized with a varying degree to automate certain features of the authoring process. We structure this survey by focusing on two key components of stories, plot and space, and more specifically the degree to which these are either automated by the computer or authored manually. By examining the successes of existing research, we identify potential new research directions in the field of computational narrative. We also identify the advantages of developing a standard model of narrative to allow for collaboration between plot and space automation techniques. This would likely benefit the field of automated space generation with the strengths in the field of automated plot generation.

Abstract Procedural modelling deals with (semi‐)automatic content generation by means of a program or procedure. Among other advantages, its data compression and the potential to generate a large variety of detailed content with reduced human intervention, have made procedural modelling attractive for creating virtual environments increasingly used in movies, games and simulations. We survey procedural methods that are useful to generate features of virtual worlds, including terrains, vegetation, rivers, roads, buildings and entire cities. In this survey, we focus particularly on the degree of intuitive control and of interactivity offered by each procedural method, because these properties are instrumental for their typical users: designers and artists. We identify the most promising research results that have been recently achieved, but we also realize that there is far from widespread acceptance of procedural methods among non‐technical, creative professionals. We conclude by discussing some of the most important challenges of procedural modelling.

The use of procedural content generation (PCG) techniques in game development has been mostly restricted to very specific types of game elements. PCG has seldom been deployed for generating entire game levels, a notable exception to this being dungeons: a specific type of game level often encountered in adventure and role playing games. Due to their peculiar combination of pace, gameplay, and game spaces, dungeon levels are among the most suited to showcase the benefits of PCG. This paper surveys research on procedural methods to generate dungeon game levels. We summarize common practices, discuss pros and cons of different approaches, and identify a few promising challenges ahead. In general, what current procedural dungeon generation methods are missing is not performance, but more powerful, accurate, and richer control over the generation process. Recent research results seem to indicate that gameplay-related criteria can provide this high-level control. However, this area is still in its infancy, and many research challenges still lie ahead, e.g., improving the intuitiveness and accessibility of such methods for designers. We also observe that more research is needed into generic mechanisms for automating the generation of the actual dungeon-geometric models. We conclude that the foundations for enabling gameplay-based control of dungeon-level generation are worth being researched, and that its promising results may be instrumental in bringing PCG into mainstream game development.

ABSTRACT Game developers are often faced with very demanding requirements on huge numbers of agents moving naturally through increasingly large and detailed virtual worlds. With the advent of multi‐core architectures, new approaches to accelerate expensive pathfinding operations are worth being investigated. Traditional single‐processor pathfinding strategies, such as A*and its derivatives, have been long praised for their flexibility. We implemented several parallel versions of such algorithms to analyze their intrinsic behavior, concluding that they have a large overhead, yield far from optimal paths, do not scale up to many cores or are cache unfriendly. In this article, we proposeParallel Ripple Search, a novel parallel pathfinding algorithm that largely solves these limitations. It utilizes a high‐level graph to assign local search areas to CPU cores at “equidistant” intervals. These cores then use A*flooding behavior to expand towards each other, yielding good “guesstimate points” at border touch on. The process does not rely on expensive parallel programming synchronization locks but instead relies on the opportunistic use of node collisions among cooperating cores, exploiting the multi‐core's shared memory architecture. As a result, all cores effectively run at full speed until enough way‐points are found. We show that this approach is a fast, practical and scalable solution and that it flexibly handles dynamic obstacles in a natural way. Copyright © 2012 John Wiley & Sons, Ltd.

In computer games and simulations, content is often rather static and rigid. As a result, its prescripted nature can lead to predictable and impersonal gameplay, while alienating unconventional players. Adaptivity in games has therefore been recently proposed to overcome these shortcomings and make games more challenging and appealing. In this paper, we survey present research on game adaptivity, identifying, and discussing the main challenges, and pointing out some of the most promising directions ahead. We first survey the purposes of adaptivity, as the principles that could steer an adaptation and generation engine. From this perspective, we proceed to thoroughly discuss adaptivity's targets and methods. Current advances and successes in this emerging field point to many yet unexplored research opportunities. Among them, we discuss the use of gameplay expectations, learning preferences, and assessment data in the integrated adaptation of game worlds, scenarios, and quests. We conclude that, among other methods, procedural content generation and semantic modeling can powerfully combine to create offline customized content and online adjustments to game worlds, scenarios, and quests. These and other promising methods, deserving ample research efforts, can therefore, be expected to significantly contribute towards making games and simulations even more unpredictable, effective, and fun.

The eight papers in this special issue focus on procedural content generation in games. They present a good combination of surveys, conceptual frameworks, innovative methods, and applications.

Computer games often take place in extensive virtual worlds, attractive for roaming and exploring. Unfortunately, current virtual cities can strongly hinder this kind of gameplay, since the buildings they feature typically have replicated interiors, or no interiors at all. Procedural content generation is becoming more established, with many techniques for automatically creating specific building elements. However, the integration of these techniques to form complete buildings is still largely unexplored, limiting their application to open game worlds. We propose a novel approach that integrates existing procedural techniques to generate such buildings. With minimal extensions, individual techniques can be coordinated to create buildings with consistently interrelated exteriors and interiors, as in the real world. Our solution offers a framework where various procedural techniques communicate with a moderator, which is responsible for negotiating the placement of building elements, making use of a library of semantic classes and constraints. We demonstrate the applicability of our approach by presenting several examples featuring the integration of a façade shape grammar, two different floor plan layout generation techniques, and furniture placement techniques. We conclude that this approach allows one to preserve the individual qualities of existing procedural techniques, while assisting the consistency maintenance of the generated buildings.

No abstract available.

Virtual outdoor terrain used for games is generally created by a level designer, using a variety of tools. These tools are currently based either on local interactive brush-based terrain sculpting or on global, parameterized algorithmic synthesis/adaptation of complete heightfields. Both tool types have largely complementary benefits and drawbacks. In this paper, we present procedural brushes, which combine the strengths of both tool types, offering a seamless transition from local control to fully automated generation, depending on the brush size. To optimize the execution speed of the computationally-intensive procedural algorithms, we propose to use the huge processing power of today's graphics hardware. For this, the procedural algorithms have been translated to shaders, and are used as part of a pipeline to render changes on a heightfield in video memory. We present a GPU brush editing pipeline for graphics hardware supporting Shader Model 3.0, coping with hardware restrictions regarding blend modes, precision and texture size. Several implemented procedural algorithms are described as well, two of which are novel. Experiments showed that the implemented system resulted in a speedup of roughly one order of magnitude over a reference CPU pipeline implementation. This made it possible for users to apply both trivial and complex procedural brushes at interactive rates, thus leading to a more efficient creation of complex virtual worlds.

Current parametric modeling systems suffer from the persistent naming problem, which is responsible for the unpredictable, sometimes stunning, behavior of such systems when re-evaluating a model, even after simple editing operations. This paper claims that the problem is an inherent difficulty of history-based parametric modeling, and that it is of little use to insist on developing more and more persistent naming schemes which end up solving only a fraction of the problem. Instead, it is argued that the rationale behind such schemes should itself be revised. Alternative approaches to define a parametric model based on persistent parametric entities can, in fact, eliminate the use of references to non-persistent geometric model entities, which is the cause of the problem. One such approach is described here, which is able to take full advantage of parametric solid modeling. It provides persistent entities in the parametric definition domain, which can be safely and consistently referred to. A number of examples illustrate how user specification of modeling operations can be performed through the interaction with a declarative feature model.

Abstract Feature modelling is now the predominant way of modelling products. Feature visualization is an important aspect here that can still be considerably improved. In this paper, an integrated way of visualizing feature models is presented, using new techniques for both the geometry and the structure of models. For the geometry of feature models, techniques are presented to visualize a selected subset of form features in a way that clearly distinguishes them from the rest of the model, as well as functional information such as closure faces of subtractive form features. For the structure of features models, techniques are presented to visualize several types of graphs. The different visualization techniques are used in an integrated way. Implementation of some of the techniques requires a non‐manifold representation of the geometry of the feature model. This representation, and some other implementation aspects, are briefly described. Throughout the paper, numerous examples of images of feature models are given which show that the new visualization techniques can indeed improve the effectiveness of feature modelling. ACM CSS: I.3.7 Three‐Dimensional Graphics and Realism—visible line/surface algorithms, J.6 Computer‐AidedEngineering—feature modelling

An approach is presented to define a family of objects in parametric modelling. It avoids an inherent problem of boundary re-evaluation in current parametric modelling systems. Even more important, it offers an effective way to define the properties, or semantics of a family of objects. A family of objects is defined by a prototype feature model, including several types of constraints to precisely specify its semantics. A family membership test is used to check whether an instance corresponding to a particular set of parameter values belongs to a family. The underlying geometric representation is a non-manifold cellular model.