Game AI designers must manage complex interactions between the AI character, the game world, and the player, while achieving their design visions. Computational co-creativity tools can aid them, but first, AI and HCI researchers must gather requirements and determine design heuristics to build effective co-creative tools. In this work, we present a participatory design study that categorizes and analyzes game AI designers' workflows, goals, and expectations for such tools. We evince deep connections between game AI design and the design of co-creative tools, and present implications for future co-creativity tool research and development.
CCS CONCEPTS• Human-centered computing → Heuristic evaluations; Participatory design; • Applied computing → Computer games; • Software and its engineering → Requirements analysis.
Interactivity and player experience are inextricably entwined with the creation of compelling narratives for interactive digital media. Narrative shapes and buttresses many such experiences, and therefore designers must construct compelling narrative arcs while carefully considering the effects of interaction on both the story and the player. As the narrative becomes more structurally complex, due to choice-based branching and other player actions, designers need to employ commensurately capable models and visualizations to keep track of that growing complexity. However, previous models of interactive narrative have failed to fully capture interactive elements with automated, operationalized visualizations. In this paper, we describe an algorithm for automated construction of a framework-driven, graph-based representation of interactive narrative. This representation more fully and transparently models structural and interactive features of the narrative than did prior approaches. We present an initial evaluation of this representation, based on modified cognitive walkthroughs performed by interactive narrative design and research experts from our research team, and we describe the takeaways for future improvement on interactive narrative modeling and analysis. CCS CONCEPTS • Computing methodologies → Knowledge representation and reasoning; Simulation evaluation; • Applied computing → Computer games; • Software and its engineering → Design languages.
Analysis of interactive narrative is a complex undertaking, requiring understanding of the narrative's design, its affordances, and its impact on players. Analysis is often performed by an expert, but this is expensive and difficult for complex interactive narratives. Automated analysis of structure, the organization of interaction elements, could help augment an expert's analysis. For this purpose we developed a model consisting of a set of metrics to analyze interactive narrative structure, enabled by a novel multi-graph representation. We implemented this model for an interactive scenario authoring tool called StudyCrafter and analyzed 20 student-designed scenarios. We show that the model illuminates the structures and groupings of the scenarios. This work provides insight for manual analysis of attributes of interactive narratives and a starting point for automated design assistance.
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