{"title":"The Intentional Fast-Forward Narrative Planner","authors":"Stephen G. Ware","doi":"10.1609/aiide.v8i2.12538","DOIUrl":"https://doi.org/10.1609/aiide.v8i2.12538","url":null,"abstract":"\u0000 \u0000 The Intentional Fast-Forward (IFF) planner is an attempt to apply fast forward-chaining state-space search methods to intentional planning---planning such that every action is directed toward some character's goal. The IFF heuristic is based on Hoffmann's original Fast Forward heuristic (2001), which solves a simplified version of the problem and uses that solution as a guide for the real problem. IFF incorporates constraints imposed by intentional planning to narrow down the set of steps which can be taken next, and it identifies fruitless branches of the search space early.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126948428","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":"Embracing the Bias of the Machine: Exploring Non-Human Fitness Functions","authors":"Arne Eigenfeldt","doi":"10.1609/aiide.v8i4.12561","DOIUrl":"https://doi.org/10.1609/aiide.v8i4.12561","url":null,"abstract":"\u0000 \u0000 Autonomous aesthetic evaluation is the Holy Grail of generative music, and one of the great challenges of computational creativity. Unlike most other computational activities, there is no notion of optimality in evaluating creative output: there are subjective impressions involved, and framing obviously plays a big role. When developing metacreative systems, a purely objective fitness function is not available: the designer is thus faced with how much of their own aesthetic to include. Can a generative system be free of the designer’s bias? This paper presents a system that incorporates an aesthetic selection process that allows for both human-designed and non-human fitness functions.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128240775","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":"Expansion on Description-Based Design of Melodies","authors":"Avneesh Sarwate, R. Fiebrink","doi":"10.1609/aiide.v9i5.12643","DOIUrl":"https://doi.org/10.1609/aiide.v9i5.12643","url":null,"abstract":"\u0000 \u0000 This work-in-progress paper describes attempted improvements on Pachet’s Description-Based Design (DBD), a system that uses machine learning to generate melodies. We discuss in depth both Description-Based Design and our extensions to Pachet’s original approach. We also present a user study in which users had some success in transforming melodies and describe the implications of these results for future work.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"2007 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128930251","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":"Toward a Computational Model of Character Personality for Planning-Based Narrative Generation","authors":"Julio César Bahamón","doi":"10.1609/aiide.v8i6.12487","DOIUrl":"https://doi.org/10.1609/aiide.v8i6.12487","url":null,"abstract":"\u0000 \u0000 Authoring narrative content for interactive digital media can be both difficult and time consuming.The research proposed here aims at enhancing the capabilities of content creators through the development of a computational model that improves the quality of automatically generated stories, potentially decreasing the burden placed on the author. The quality and believability of a story can be significantly enhanced by the presence of compelling characters. To achieve this objective, I aim to develop a choice-based computational model that facilitates the automatic generation of narrative that includes characters that are made more compelling by the presence of distinct personality characteristics.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125547178","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}
Alok Baikadi, Jonathan P. Rowe, Bradford W. Mott, James C. Lester
{"title":"Toward Narrative Schema-Based Goal Recognition Models for Interactive Narrative Environments","authors":"Alok Baikadi, Jonathan P. Rowe, Bradford W. Mott, James C. Lester","doi":"10.1609/aiide.v8i2.12534","DOIUrl":"https://doi.org/10.1609/aiide.v8i2.12534","url":null,"abstract":"\u0000 \u0000 Computational models for goal recognition hold great promise for enhancing the capabilities of drama managers and director agents for interactive narratives. The problem of goal recognition, and its more general form, plan recognition, have been the subjects of extensive investigation in the AI community. However, relatively little effort has been undertaken to examine goal recognition in interactive narrative. In this paper, we propose a research agenda to improve the accuracy of goal recognition models for interactive narratives using explicit representations of narrative structure inspired by the natural language processing community. We describe a particular category of narrative representations, narrative schemas, that we anticipate will effectively capture patterns of player behavior in interactive narratives and improve the accuracy of goal recognition models.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121611130","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 Review of Student Modeling Techniques in Intelligent Tutoring Systems","authors":"Brent E. Harrison, D. Roberts","doi":"10.1609/aiide.v8i5.12574","DOIUrl":"https://doi.org/10.1609/aiide.v8i5.12574","url":null,"abstract":"\u0000 \u0000 In this paper, we survey techniques used in intelligent tutoring systems (ITSs) to model student knowledge. The three techniques that we review in detail are knowledge tracing, performance factor analysis, and matrix factorization. We also briefly cover other techniques that have been used. This review is meant to be a repository of knowledge for those who want to integrate these techniques into serious games. It is also meant to increase awareness and interest as to the techniques available that can be integrated into serious games.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"87 2-3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116278799","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":"Inferring Performer Skill from Aesthetic Quality Features in a Dance Game Gesture Corpus","authors":"Christopher Maraffi, Sascha Ishikawa, A. Jhala","doi":"10.1609/aiide.v9i2.12585","DOIUrl":"https://doi.org/10.1609/aiide.v9i2.12585","url":null,"abstract":"\u0000 \u0000 In this paper, we describe experiments for inferring the artistic skill of performers by analyzing pose features in a gesture corpus. Poses were generated by having participants play a popular Kinect dance game in a markerless motion capture studio. Skeletal data was analyzed for features derived from both statistical analysis as well as arts and animation theory, and aesthetic metrics were designed to score pose features along three dimensions: balance,asymmetry, and readability. We applied our metrics to poses in a corpus of 10,080 annotated frames generated from 20 dance performances ranked according to the performing arts background of each participant. This work is the foundation of a computational performatology approach to quantifying artistic gesture in media by identifying aesthetic features that indicate figurative quality to viewers. The potential application of gesture analysis and feedback will be to inform the design of performative logics for virtual controlof avatars and non-player characters in videogames.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116863577","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":"Incorporating Search Algorithms into RTS Game Agents","authors":"David Churchill, M. Buro","doi":"10.1609/aiide.v8i3.12548","DOIUrl":"https://doi.org/10.1609/aiide.v8i3.12548","url":null,"abstract":"\u0000 \u0000 Real-time strategy (RTS) games are known to be one of the most complex gamegenres for humans to play, as well as one of the most difficult games forcomputer AI agents to play well. To tackle the task of applying AI to RTSgames, recent techniques have focused on a divide-and-conquer approach,splitting the game into strategic components, and developing separate systemsto solve each. This trend gives rise to a new problem: how to tie thesesystems together into a functional real-time strategy game playing agent. Inthis paper we discuss the architecture of UAlbertaBot, our entry into the 2011/2012 StarCraft AI competitions, and the techniques used to include heuristic search based AI systems for the intelligent automation of both build order planning and unit control for combat scenarios.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115065608","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":"Producing Immersive Interactive Narratives in Complex 3D Open Worlds","authors":"Alexander Shoulson","doi":"10.1609/aiide.v9i6.12604","DOIUrl":"https://doi.org/10.1609/aiide.v9i6.12604","url":null,"abstract":"\u0000 \u0000 Interactive virtual worlds present a unique opportunity for simulation, training, and entertainment in settings that are otherwise prohibitive to recreate or control. In order to produce a truly immersive experience, it is important to populate these 3D environments with fully articulated virtual humans capable of exhibiting functional, purposeful behavior and complex interactions with other objects in the environment. In this paper, we discuss the challenges inherent in conducting interactive narratives in rich virtual worlds with autonomous characters, and present our ongoing work on dynamic story generation using the event-centric authoring paradigm. Unlike traditional character behavior systems, events enable an author to design character interactions using a centralized control structure that temporarily co-opts character autonomy and treats participants as limbs of the same entity. This allows us to create a narrative action space based on complex occurrences an author would like to see in the world, like a riot or protest, rather than in the space of individual character actions like opening a door.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127004601","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":"Improving Behaviour and Decision Making for Companions in Modern Digital Games","authors":"Jonathan Tremblay","doi":"10.1609/aiide.v9i6.12602","DOIUrl":"https://doi.org/10.1609/aiide.v9i6.12602","url":null,"abstract":"\u0000 \u0000 Non-player character companions in video games should cooperate with players, understand them, and follow their lead during gameplay. In current games, however, companions tend to exhibit mainly static behaviours, and rarely live up to player expectations. In general, our work is aimed at improving this situation, developing both techniques and tools which allow companion NPCs to behave more appropriately, respecting player preferences and offering a more immersive gameplay for players.\u0000 \u0000","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126563104","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}