With increasing technological capabilities, video games provide ever more expan-sive virtual worlds for players to explore. Designers employ various mechanics and level design principles to encourage such exploration. However, what moti-vates people to explore in virtual environments, and which approaches are success-ful, is not yet clearly established. Methods for measuring player experience often take place retroactively after a play session, relying on recall, and are thus prone to missing less salient events and their motivations. Journaling events as they occur allow promises to be a suitable method of collecting data, but presents a challenge in aggregating data points due to their freeform nature. This makes it difficult to identify overarching patterns of exploration behaviour. We present an exploratory study in devising a journaling protocol for gathering information during game-play sessions, focused on documenting moments of exploration in a manner that balances ease of data capture and data evaluation. We describe our efforts in proto-typing this journaling method and how we used it to analyse Cyberpunk 2077 and several other game designs. Our results show that exploration occurs in a pattern of event → expectation → resolution. The motivation to explore depends on the expectations that a game raises through its marketing and design. At the same time, exploratory behaviour going unrewarded by the game quickly reduces the desire to explore. When recording instances of exploration, the addition of emotion words is essential in order to properly contextualize the information. This arti-cle lays the foundation for documenting exploration in games, as well as other emotional or behavioural constructs that require in-the-moment data collection.@en

—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.@en

With hybrid board games rising in popularity and game AI algorithms becoming more sophisticated, there is potential in involving AI to create novel game experiences and tools that can support developers. However, examples of hybrid board games that involve AI remain relatively sparse. In this work, we propose that creating a taxonomy of AI in hybrid board games can help the development of games that occupy as-of-yet unexplored areas of the design space. By mapping out different dimensions through which the involvement of AI in such games can be understood, we seek to encourage further academic discussions and applied explorations.@en

Sport games are among the oldest and best established genres of computer games. Sport-inspired environments, such as RoboCup, have been used for AI benchmarking for years. We argue that, in spite of the rise of increasingly more sophisticated game genres, team sport games will remain an important testbed for AI benchmarking due to two primary factors. First, there are several genre-specific challenges for AI systems that are neither present nor emphasized in other types of games, such as team AI and frequent replanning. Second, there are unmistakable nonskill-related goals of AI systems, contributing to player enjoyment, that are most easily observed and addressed within a context of a team sport, such as showing creative and emotional traits. We analyze these factors in detail and outline promising directions for future research for game AI benchmarking, within a team sport context. @en