Procedural content generation (PCG)-based game design aims to reach a new way of playing games by focusing gameplay around algorithmic game content generation. However, positioning interaction with PCG systems and generated content to the center of player experience poses design challenges for both game design and AI design. In order to create the wanted affordances, rich contextual information is required to make informed decisions on the generated content. While previous research has presented excellent developments on PCG's possibilities, further considering context and affordances in the early stages of prototyping may aid designers reach these possibilities in a more consistent manner. This study is set to discuss how context, affordances and the game's overall design can be considered during the prototyping process of PCGbased games. Misaligned game context and affordances can result in deeply rooted design issues that may later manifest as subpar gameplay experiences and increased development effort. These emergent issues are examined through a post-mortem case study to produce an extended PCG-based design process, featuring actionable steps, that takes context, affordances, and the game's overall design into account through meaningful play. CCS CONCEPTS • Applied computing → Computer games.

Digital twin (DT) emerges as a key concept of the Industry 4.0 paradigm and beyond. However, the current literature lacks focus on humans and human activities as a part of complex system DTs. Acknowledging human aspects in DTs can enhance work performance, well-being, motivation and personal development of professionals. This study examines emerging requirements for human digital twins (HDTs) in three use cases of industry-academia collaboration on complex systems. The results draw together the overall design problem and four design objectives for HDTs. We propose to combine the machine and human-related aspects of DTs, and highlight the need for virtual-to-virtual interoperability between HDTs and machines alike. Furthermore, we outline differences between humans and machines regarding digital twinning by addressing human activities and knowledge-based behavior on systems. Design of HDTs requires understanding of individual professional characteristics, such as skills and information preferences, together with twinning between the physical and digital machine entities and interactions between the human and machine DTs. As the field moves towards including humans as a part of the DT concept, incorporating HDTs in complex systems emerges as an increasingly significant issue.

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