Learning the Designer's Preferences to Drive Evolution

This paper presents the Designer Preference Model, a data-driven solution that pursues to learn from user generated data in a Quality-Diversity Mixed-Initiative Co-Creativity (QD MI-CC) tool, with the aims of modelling the user's design style to better assess the tool's procedurally generated content with respect to that user's preferences. Through this approach, we aim for increasing the user's agency over the generated content in a way that neither stalls the user-tool reciprocal stimuli loop nor fatigues the user with periodical suggestion handpicking. We describe the details of this novel solution, as well as its implementation in the MI-CC tool the Evolutionary Dungeon Designer. We present and discuss our findings out of the initial tests carried out, spotting the open challenges for this combined line of research that integrates MI-CC with Procedural Content Generation through Machine Learning.Comment: 16 pages, Accepted and to appear in proceedings of the 23rd European Conference on the Applications of Evolutionary and bio-inspired Computation, EvoApplications 202

Towards Friendly Mixed Initiative Procedural Content Generation: Three Pillars of Industry

While the games industry is moving towards procedural content generation (PCG) with tools available under popular platforms such as Unreal, Unity or Houdini, and video game titles like No Man’s Sky and Horizon Zero Dawn taking advantage ofPCG, the gap between academia and industry is as wide as it has ever been, in terms of communication and sharing methods. One of the authors, has worked on both sides of this gap and in an effort to shorten it and increase the synergy between the two sectors, has identified three design pillars for PCG using mixed-initiative interfaces. The three pillars are Respect Designer Control, Respect the Creative Process and Respect Existing Work Processes. Respecting designer control is about creating a tool that gives enough control to bring out the designer’s vision. Respecting the creative process concerns itself with having a feedback loop that is short enough, that the creative process is not disturbed. Respecting existing work processes means that a PCG tool should plug in easily to existing asset pipelines. As academics and communicators, it is surprising that publications often do not describe ways for developers to use our work or lack considerations for how a piece ofwork might fit into existing content pipelines

Can computers foster human users' creativity? Theory and praxis of mixed-initiative co-creativity

This article discusses the impact of artificially intelligent computers to the process of design, play and educational activities. A computational process which has the necessary intelligence and creativity to take a proactive role in such activities can not only support human creativity but also foster it and prompt lateral thinking. The argument is made both from the perspective of human creativity, where the computational input is treated as an external stimulus which triggers re-framing of humans’ routines and mental associations, but also from the perspective of computational creativity where human input and initiative constrains the search space of the algorithm, enabling it to focus on specific possible solutions to a problem rather than globally search for the optimal. The article reviews four mixed-initiative tools (for design and educational play) based on how they contribute to human-machine co-creativity. These paradigms serve different purposes, afford different human interaction methods and incorporate different computationally creative processes. Assessing how co-creativity is facilitated on a per-paradigm basis strengthens the theoretical argument and provides an initial seed for future work in the burgeoning domain of mixed-initiative interaction.peer-reviewe

Can computers foster human users' creativity? Theory and praxis of mixed-initiative co-creativity

This article discusses the impact of artificially intelligent computers to the process of design, play and educational activities. A computational process which has the necessary intelligence and creativity to take a proactive role in such activities can not only support human creativity but also foster it and prompt lateral thinking. The argument is made both from the perspective of human creativity, where the computational input is treated as an external stimulus which triggers re-framing of humans’ routines and mental associations, but also from the perspective of computational creativity where human input and initiative constrains the search space of the algorithm, enabling it to focus on specific possible solutions to a problem rather than globally search for the optimal. The article reviews four mixed-initiative tools (for design and educational play) based on how they contribute to human-machine co-creativity. These paradigms serve different purposes, afford different human interaction methods and incorporate different computationally creative processes. Assessing how co-creativity is facilitated on a per-paradigm basis strengthens the theoretical argument and provides an initial seed for future work in the burgeoning domain of mixed-initiative interaction.peer-reviewe

Pitako -- Recommending Game Design Elements in Cicero

Recommender Systems are widely and successfully applied in e-commerce. Could they be used for design? In this paper, we introduce Pitako1, a tool that applies the Recommender System concept to assist humans in creative tasks. More specifically, Pitako provides suggestions by taking games designed by humans as inputs, and recommends mechanics and dynamics as outputs. Pitako is implemented as a new system within the mixed-initiative AI-based Game Design Assistant, Cicero. This paper discusses the motivation behind the implementation of Pitako as well as its technical details and presents usage examples. We believe that Pitako can influence the use of recommender systems to help humans in their daily tasks.Comment: Paper accepted in the IEEE Conference on Games 2019 (COG 2019