text: 60,66,1149118095836925952,19510090,Julian Togelius,"How could AI help you design games? Perhaps by giving you helpful suggestions as you design? In a new paper, we introduce Pitako, a recommender system for game design. The system learns from existing games to suggest design elements. <LINK> <LINK> Thin of this as something akin to Amazon's, Netflix's, or Spotify's recommendations, but for game design. The system has a library of more than a hundred games, and when it recognizes a design pattern from existing games, it suggests elements to include, and from which game. <LINK> So, if you are creating a space-themed shooter and have created spaceships and aliens, it suggests that you may want a missile and a firing mechanic. Of course, you may not want that - you may want to make a nonviolent game, so feel free to ignore the suggestion. But Pitako takes its cues from existing games in its database, and those are mostly reimplemented versions of classic arcade games. To make all this possible, we build on the @gvgai framework, which includes loads of games implemented in the Video Game Description Language. The nice thing about building on VGDL is that we can recommend rules as well as sprites and behavior, and we can abstract from specific implementations in individual games to general rules. At the core, we use the classic Apriori algorithm for this. <LINK> Finally, Pitako also recommends where to place sprites in levels. Again, this is based on patterns extracted from the levels of existing games, but augmented with a few heuristics. <LINK> The paper, by @Jaspier @dgopstein @nealen and myself, will be presented at @cog2019ieee, which is gearing up to be a really fantastic conference. You should be there. Technically, Pitako is a sub-system of Cicero, a versatile tool for AI-assisted design built on the GVGAI framework and the VGDL language. Some previous work on Cicero can be found here: <LINK>",https://arxiv.org/abs/1907.03877,"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. ",Pitako -- Recommending Game Design Elements in Cicero,8,"['How could AI help you design games? Perhaps by giving you helpful suggestions as you design? In a new paper, we introduce Pitako, a recommender system for game design. The system learns from existing games to suggest design elements.\n<LINK> <LINK>', ""Thin of this as something akin to Amazon's, Netflix's, or Spotify's recommendations, but for game design. The system has a library of more than a hundred games, and when it recognizes a design pattern from existing games, it suggests elements to include, and from which game. https://t.co/f3nwXR2c9s"", 'So, if you are creating a space-themed shooter and have created spaceships and aliens, it suggests that you may want a missile and a firing mechanic. Of course, you may not want that - you may want to make a nonviolent game, so feel free to ignore the suggestion.', 'But Pitako takes its cues from existing games in its database, and those are mostly reimplemented versions of classic arcade games. To make all this possible, we build on the @gvgai framework, which includes loads of games implemented in the Video Game Description Language.', 'The nice thing about building on VGDL is that we can recommend rules as well as sprites and behavior, and we can abstract from specific implementations in individual games to general rules. At the core, we use the classic Apriori algorithm for this. https://t.co/KuRTaLisKq', 'Finally, Pitako also recommends where to place sprites in levels. Again, this is based on patterns extracted from the levels of existing games, but augmented with a few heuristics. https://t.co/ChEOs1hjlZ', 'The paper, by @Jaspier @dgopstein @nealen and myself, will be presented at @cog2019ieee, which is gearing up to be a really fantastic conference. You should be there.', 'Technically, Pitako is a sub-system of Cicero, a versatile tool for AI-assisted design built on the GVGAI framework and the VGDL language. Some previous work on Cicero can be found here:\nhttps://t.co/j2Ap9G3jBZ']",19,07,1875