{"title":"Crosston Tavern: Modulating Autonomous Characters Behaviour through Player-NPC Conversation","authors":"Elisabeth Oliver, Michael Mateas","doi":"10.1609/aiide.v17i1.18906","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18906","url":null,"abstract":"NPCs (Non-Player Characters) are a staple of video games, filling all kinds of supporting roles. This work seeks to flip that paradigm and place the player in the role of support for the goals of a small collection of NPCs enabling a new kind of AI-driven gameplay. Built on a world simulation where NPCs can take action according to their goals and knowledge of the world state and a conversation space in which the NPC is able to report their actions and exchange information with the player, this prototype AI-based game design explores a new player-NPC interaction in which player conversational actions indirectly influence the NPC simulation. In this paper we discuss the architecture, provide a design postmortem, and report the results of play testing.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"4 1","pages":"179-186"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82049293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Demonstration of KiaiTime: A Mixed-Initiative PCGML Rhythm Game Editor","authors":"Emily Halina, Matthew J. Guzdial","doi":"10.1609/aiide.v17i1.18916","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18916","url":null,"abstract":"Chart creation for rhythm action games is a time consuming task that requires specialized design knowledge. While chart generation systems have been explored in the past, there are currently no co-creative chart authoring systems. In this paper, we present KiaiTime, a mixed-initiative, co-creative PCGML editor for the rhythm game Taiko no Tatsujin. KiaiTime allows the user to interface with an AI partner that acts as a source of guidance and inspiration in the chart creation process.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"19 1","pages":"240-242"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81670031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adrián González-Casillas, Matthew J. Guzdial, Félix Ramos
{"title":"A Tool for Generating Monster Silhouettes with a Word-Conditioned Variational Autoencoder","authors":"Adrián González-Casillas, Matthew J. Guzdial, Félix Ramos","doi":"10.1609/aiide.v17i1.18915","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18915","url":null,"abstract":"A character’s appearance is crucial to communicating game mechanics to the audience. Creating a game character’s design is a time-consuming task and requires design knowledge, skills, and experience. Research on how an AI system might be able to support this design process is an underexplored area. In this work we present a prototype of a variational autoencoder-based creativity support tool that modifies game character silhouettes by using words to describe the design’s desired properties.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"359 1","pages":"237-239"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80205111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ross Mawhorter, Batu Aytemiz, Isaac Karth, Adam M. Smith
{"title":"Content Reinjection for Super Metroid","authors":"Ross Mawhorter, Batu Aytemiz, Isaac Karth, Adam M. Smith","doi":"10.1609/aiide.v17i1.18905","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18905","url":null,"abstract":"Academic procedural content generation (PCG) efforts often yield plausible game content but stop short of fully integrating it into the games that inspired it. This misses opportunities to discover game- and platform-specific constraints that were previously ignored in evaluations of playability (e.g. how invisible objects in a level design are used to explicitly control camera movement). Grappling with existing games can ensure that the PCG community is solving realistic problems, rather than convenient abstractions of them. In this paper, we use technical knowledge from the ROM hacking community along with the WaveFunctionCollapse example-driven generator to reinject controllably-generated level designs into the commercial Super Metroid ROM image (rather than a clone) for execution on physical Nintendo hardware. Our work charts a path for more realistic evaluation of the playability of generated content and highlights challenges for deploying generative methods. These challenges can spark a conversation about the ways that abstractions are used in PCG research.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"21 1","pages":"172-178"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85009802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Robert Zubek, I. Horswill, Ethan Robison, Matthew Viglione
{"title":"Social Modeling via Logic Programming in City of Gangsters","authors":"Robert Zubek, I. Horswill, Ethan Robison, Matthew Viglione","doi":"10.1609/aiide.v17i1.18912","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18912","url":null,"abstract":"City of Gangsters is a commercial strategy game with significant social modeling mechanics: it is a tycoon management game, where the player needs to work their social connections with a network of roughly 1200 NPCs to get things done, and NPC opinions about the player modulate the player's ability to succeed.\u0000\u0000We found logic programming to be well suited to our knowledge representation problem, including the need to perform inferences over a relationship network with more than a thousand active characters, and to provide the player with meaningful feedback about the consequences of their actions in the social space.\u0000\u0000In this paper we present the technical details of this social modeling problem, the details of our logic programming implementation, and how this interacts with the game's design and its social and material economies.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"55 1","pages":"220-226"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73413290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Athar Mahmoudi-Nejad, Matthew J. Guzdial, P. Boulanger
{"title":"Arachnophobia Exposure Therapy using Experience-driven Procedural Content Generation via Reinforcement Learning (EDPCGRL)","authors":"Athar Mahmoudi-Nejad, Matthew J. Guzdial, P. Boulanger","doi":"10.1609/aiide.v17i1.18904","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18904","url":null,"abstract":"Personalized therapy, in which a therapeutic practice is adapted to an individual patient, leads to better health outcomes. Typically, this is accomplished by relying on a therapist's training and intuition along with feedback from a patient. While there exist approaches to automatically adapt therapeutic content to a patient, they rely on hand-authored, pre-defined rules, which may not generalize to all individuals. In this paper, we propose an approach to automatically adapt therapeutic content to patients based on physiological measures. We implement our approach in the context of arachnophobia exposure therapy, and rely on experience-driven procedural content generation via reinforcement learning (EDPCGRL) to generate virtual spiders to match an individual patient. In this initial implementation, and due to the ongoing pandemic, we make use of virtual or artificial humans implemented based on prior arachnophobia psychology research. Our EDPCGRL method is able to more quickly adapt to these virtual humans with high accuracy in comparison to existing, search-based EDPCG approaches.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"1 1","pages":"164-171"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74135113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Curve-Based Level Generation for a Full-Body VR Rhythm Game","authors":"E. J. Truesdell","doi":"10.1609/aiide.v17i1.18918","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18918","url":null,"abstract":"Due to the large amount of content authoring required to produce levels for rhythm games, procedural content generation provides an attractive alternative for generating levels in large numbers. Frequently, however, level generators for rhythm games rely only on a “difficulty” measure to describe desired level properties. This work presents level generation tool for BEAMS, a full-body virtual reality rhythm game. The BEAMS level generator allows designers to shape curves describing four characteristics of the obstacles needed for a game in which the primary interaction involves the human body in three-dimensional space.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"48 4 1","pages":"246-248"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75697610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-Agent Cooperation in Games with Goal Oriented Action Planner: Use Case in WONDER Prototype Project","authors":"Gautier Boeda","doi":"10.1609/aiide.v17i1.18909","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18909","url":null,"abstract":"Multi-agent cooperation systems often rely on an external commander-like entity that will plan for all the agents it manages. When it comes to games development, this entity can be hidden from the player, which makes the player believe the characters are actually taking their own decisions. However, it has limitations. We believe that to achieve truly believable character-interactions between non-playable characters, real(non-scripted) communication between the agents is the key. We will introduce our multi-agent cooperation system where each AI-agent thinks for itself and communicates with the other agents to cooperate and achieves complex goals. The system will be demonstrated with a use case in our WONDER prototype project.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"5 1","pages":"204-207"},"PeriodicalIF":0.0,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72758045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"HPA* Enhancements","authors":"M. Jansen, M. Buro","doi":"10.1609/aiide.v3i1.18791","DOIUrl":"https://doi.org/10.1609/aiide.v3i1.18791","url":null,"abstract":"In video games, pathfinding must be done quickly and accurately. Not much computational time is allowed for pathfinding, but realistic looking paths are required. One approach to pathfinding which attempts to satisfy both of these constraints is to perform pathfinding on abstractions of the map. Botea et al.'s Hierarchical Pathfinding A* (HPA*) does this by dividing the map into square sectors and defining entrances between them. Although HPA* performs quick pathfinding which produces near-optimal paths, some improvements can be introduced. Here we discuss a faster path smoothing method, an alternative way to compute the weights of abstract edges, and lazy edge weight computations.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"27 9","pages":"84-87"},"PeriodicalIF":0.0,"publicationDate":"2021-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72372440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Murtuza N. Shergadwala, Zhaoqing Teng, M. S. El-Nasr
{"title":"Can we infer player behavior tendencies from a player's decision-making data? Integrating Theory of Mind to Player Modeling","authors":"Murtuza N. Shergadwala, Zhaoqing Teng, M. S. El-Nasr","doi":"10.1609/aiide.v17i1.18908","DOIUrl":"https://doi.org/10.1609/aiide.v17i1.18908","url":null,"abstract":"Game AI systems need the theory of mind, which is the humanistic ability to infer others' mental models, preferences, and intent. Such systems would enable inferring players' behavior tendencies that contribute to the variations in their decision-making behaviors. To that end, in this paper, we propose the use of inverse Bayesian inference to infer behavior tendencies given a descriptive cognitive model of a player's decision making. The model embeds behavior tendencies as weight parameters in a player's decision-making. Inferences on such parameters provide intuitive interpretations about a player's cognition while making in-game decisions. We illustrate the use of inverse Bayesian inference with synthetically generated data in a game called textit{BoomTown} developed by Gallup. We use the proposed model to infer a player's behavior tendencies for moving decisions on a game map. Our results indicate that our model is able to infer these parameters towards uncovering not only a player's decision making but also their behavior tendencies for making such decisions.","PeriodicalId":92576,"journal":{"name":"Proceedings. AAAI Artificial Intelligence and Interactive Digital Entertainment Conference","volume":"5 1","pages":"195-202"},"PeriodicalIF":0.0,"publicationDate":"2021-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86376263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}