Collaborative agent gameplay in the Pandemic board game

While artificial intelligence has been applied to control players’ decisions in board games for over half a century, little attention is given to games with no player competition. Pandemic is an exemplar collaborative board game where all players coordinate to overcome challenges posed by events occurring during the game’s progression. This paper proposes an artificial agent which controls all players’ actions and balances chances of winning versus risk of losing in this highly stochastic environment. The agent applies a Rolling Horizon Evolutionary Algorithm on an abstraction of the game-state that lowers the branching factor and simulates the game’s stochasticity. Results show that the proposed algorithm can find winning strategies more consistently in different games of varying difficulty. The impact of a number of state evaluation metrics is explored, balancing between optimistic strategies that favor winning and pessimistic strategies that guard against losing.peer-reviewe

Cellular automata for real-time generation of infinite cave levels

This paper presents a reliable and efficient approach to procedurally generating level maps based on the self-organization capabilities of cellular automata (CA). A simple CA-based algorithm is evaluated on an infinite cave game, generating playable and well-designed tunnel-based maps. The algorithm has very low computational cost, permitting realtime content generation, and the proposed map representation provides sufficient flexibility with respect to level design.peer-reviewe

The word game : the ontology of an undefinable object

In this paper we address the problem of defining games formally, following Wittgenstein's dictum that games cannot be defined adequately as a formal category. Several influential attempts at definitions will be evaluated and shown to be inadequate. As an alternative, we propose a descriptive model of the definable supercategory that games belong to, cybermedia, that is pragmatic, open, and capable of meeting the needs of the diverse, intensely interdisciplinary field of game studies for a uniting conceptuallization of its main phenomenon. Our approach, the Cybermedia model, consisting of Player, Sign, Mechanical System, and Material Medium, offers a medium-independent, flexible and analytically useful way to contrast different approaches in games research and to determine which aspect of the phenomenon one is talking about when the word ‘game’ is used.peer-reviewe

Pairing character classes in a deathmatch shooter game via a deep-learning surrogate model

This paper introduces a surrogate model of gameplay that learns the mapping between different game facets, and applies it to a generative system which designs new content in one of these facets. Focusing on the shooter game genre, the paper explores how deep learning can help build a model which combines the game level structure and the game's character class parameters as input and the gameplay outcomes as output. The model is trained on a large corpus of game data from simulations with artificial agents in random sets of levels and class parameters. The model is then used to generate classes for specific levels and for a desired game outcome, such as balanced matches of short duration. Findings in this paper show that the system can be expressive and can generate classes for both computer generated and human authored levels.peer-reviewe

Learning the patterns of balance in a multi-player shooter game

A particular challenge of the game design process is when the designer is requested to orchestrate dissimilar elements of games such as visuals, audio, narrative and rules to achieve a specic play experience. Within the domain of adversarial rst person shooter games, for instance, a designer must be able to comprehend the dierences between the weapons available in the game, and appropriately cra a game level to take advantage of strengths and weaknesses of those weapons. As an initial study towards computationally orchestrating dissimilar content generators in games, this paper presents a computational model which can classify a matchup of a team-based shooter game as balanced or as favoring one or the other team. e computational model uses convolutional neural networks to learn how game balance is aected by the level, represented as an image, and each team’s weapon parameters. e model was trained on a corpus of over 50,000 simulated games with articial agents on a diverse set of levels created by 39 dierent generators. e results show that the fusion of levels, when processed by a convolutional neural network, and weapon parameters yields an accuracy far above the baseline but also improves accuracy compared to articial neural networks or models which use partial information, such as only the weapon or only the level as input.peer-reviewe

Modelling virtual camera behaviour through player gaze

In a three-dimensional virtual environment, aspects such as narrative and interaction largely depend on the placement and animation of the virtual camera. Therefore, virtual camera control plays a critical role in player experience and, thereby, in the overall quality of a computer game. Both game industry and game AI research focus on the development of increasingly sophisticated systems to automate the control of the virtual camera integrating artificial intelligence algorithms within physical simulations. However, in both industry and academia little research has been carried out on the relationship between virtual camera, game-play and player behaviour. We run a game user experiment to shed some light on this relationship and identify relevant differences between camera behaviours through different game sessions, playing behaviours and player gaze patterns. Results show that users can be efficiently profiled in dissimilar clusters according to camera control as part of their gameplay behaviour.peer-reviewe

Mixed-initiative co-creativity

Creating and designing with a machine: do we merely create together (co-create) or can a machine truly foster our creativity as human creators? When does such co-creation foster the co-creativity of both humans and machines? This paper investigates the simultaneous and/or iterative process of human and computational creators in a mixed-initiative fashion within the context of game design and attempts to draw from both theory and praxis towards answering the above questions. For this purpose, we first discuss the strong links between mixed-initiative co-creation and theories of human and computational creativity. We then introduce an assessment methodology of mixed-initiative co-creativity and, as a proof of concept, evaluate Sentient Sketchbook as a co-creation tool for game design. Core findings suggest that tools such as Sentient Sketchbook are not mere game authoring systems or mere enablers of creation but, instead, foster human creativity and realize mixed-initiative co-creativity.peer-reviewe

The challenge of evaluating player experience in Tabletop Role-Playing Games

Tabletop Role-Playing Games (TTRPGs) offer players the opportunity to form imaginary gameworlds and stories within them, create community, solve problems, and explore identity. Designers and researchers have tried to identify how aspects of TTRPGs facilitate collaboration, immersion, creativity, and more. However, there has been no attempt to develop a formal assessment methodology for player experience during TTRPG play. This paper argues that evaluating TTRPG players’ experience can provide vital data for Game Masters to improve on their future games, for players to reflect on their experience, and for TTRPG designers or event organizers to collect and compare data. As a first step towards developing such an evaluation method, we identify important dimensions of TTRPG play that can be meaningful to track and actionable to improve upon. Moreover, we review player experience dimensions and evaluation methods in digital games, and explore similarities and differences with TTRPGs.peer-reviewe

Village voices : an adaptive game for conflict resolution

In this paper, we describe the design and technology of Vil lage Voices, an adaptive serious game designed to support children in learning about con ict resolution. Relying on experiential learning as an underlying learning philosophy, Village Voices puts players in the role of interdependent vil lagers who need to work through the various con icts that arise in the game world. To gradually earn guru status, play ers must successfully complete various personalised quests, which require cooperation between players. The personali sation technology behind Village Voices relies upon an accu rate player model that drives the adjustment and selection of quests for each player.The research is supported, in part, by the FP7 ICT project SIREN (project no: 258453).peer-reviewe

MiniDungeons 2 : an experimental game for capturing and modeling player decisions

This paper describes MiniDungeons 2 (MD2): a turn-based rogue-like game developed to support research in capturing and modeling player decision making processes through procedural personas and using such models as critics for procedural content generation. MD2 intends to provide a full-circle framework for collecting, modeling, simulating, and producing content for player decision making styles. The fully instrumented and telemetric game will soon be made available to the public to be played on smart-phones for the purpose of collecting as many play traces, representing as many different decision making styles, as possible.peer-reviewe