This paper describes the accepted entries to the sixth PlayableExperiences track to be held at the AIIDE conference.The Playable Experiences track showcases innovative completeworks that are informed, inspired, or otherwise enabledby artificial intelligence.
Play trace dissimilarity metrics compare two plays of a game and describe how different they are from each other. But how can we evaluate these metrics? Are some more accurate than others for a particular game, or in general? If so, why? Is the appropriate metric for a given game determined by certain characteristics of the game's design? This work provides an experimental methodology for validating play trace dissimilarity metrics for conformance to game designers' perception of play trace difference. We apply this method to a game-independent metric called Gamalyzer and compare it against three baselines which are representative of commonly used techniques in game analytics. We find that Gamalyzer---with an appropriate input encoding---is more accurate than the baseline metrics for the specific game under consideration, but simpler metrics based on event counting perform nearly as well for this game.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.