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Open research questions in Artificial Intelligence in Games

107 gap statements mined from Artificial Intelligence in Games papers in our 4.5M-paper local library, which holds 647 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • The lack of engagement and replayability in current mobile dungeon crawlers. The use of simple swipe or tap interfaces, static level layouts, and predictable enemy behaviours in current mobile dungeon crawlers.

    RISE OF SHADOWS: DEVELOPMENT OF A 2D ANDROID DUNGEON CRAWLER WITH AI DRIVEN GAMEPLAY MECHANICS AND PROCEDURAL GENERATION · 2026 · DOI

  • Traditional video production is a complex, time-consuming, and resource-intensive process that requires significant technical expertise. The system needs to be able to understand natural language descriptions and generate coherent video clips. The system needs to be scalable and able to handle large amounts of data.

    AI -Powered Web Application for Automated Short Video Generation · 2026 · DOI

  • Prior approaches have limitations in capturing narrative effects. There is a need for a more nuanced understanding of narrative comprehension and its role in media recommendation.

    Computational and Machine Applications of a Narrative Theory Based Symbolic Ontology: Movie Search and Recommendation · 2026 · DOI

  • Current MARL benchmarks have limitations that hinder progress in the field. Most existing benchmarks emphasize micromanagement over strategic decision-making.

    HLSMAC: A New StarCraft Multi-Agent Challenge for High-Level Strategic Decision-Making · 2026 · DOI

  • The paper identifies the challenge of scaling imperfect-information games due to the lack of a formal task model and evaluation metric for hand abstraction. The paper notes the challenge of developing hand abstraction algorithms that can effectively incorporate historical information.

    Beyond Outcome-Based Imperfect-Recall: Higher-Resolution Abstractions for Imperfect-Information Games · 2026 · DOI

  • The paper suggests that developing signal abstraction algorithms capable of exceeding the PAOI bound and targeting the FROI bound is a critical direction for future work. The paper notes that applying the techniques to other domains that involve imperfect information and sequential decision-making is a potential area for future research.

    Beyond Outcome-Based Imperfect-Recall: Higher-Resolution Abstractions for Imperfect-Information Games · 2026 · DOI

  • Through extensive experiments, we demonstrated that while current algorithms can attain strong performance in the single-team setting, they degrade significantly when scaling to multi-team generalization – highlighting a key open challenge in multi-agent learning.

    VGC-Bench: Towards Mastering Diverse Team Strategies in Competitive Pokémon · 2026 · DOI

  • While in-game AI was not explored in this paper, it can be further studied to solo development, particularly what in-game AI algorithms can be used for easy and quick to enhance game features.

    A Comparative Study of AI Tools and Techniques for Assisting Solo Artists and Programmers in Developing Video Games from Scratch · 2026 · DOI

  • The lack of variation in the Skinner box could produce results that are specific to a narrow set of conditions, thus giving rise to a failure to reproduce an effect when task characteristics change even modestly. The use of video game engines may not be suitable for all types of behavioral research, and the cost and complexity of creating immersive environments may be a limitation.

    Video game engines as the new “virtual” Skinner box · 2026 · DOI

  • The limitations of the Skinner box, including its lack of flexibility and control, have led to the need for more advanced methods. The need for more immersive and engaging environments for behavioral research has led to the exploration of alternative approaches, such as video game engines.

    Video game engines as the new “virtual” Skinner box · 2026 · DOI

  • The limitation of behavior in non-player characters in games is a major issue. The lack of a qualitative intellectual component in game characters can lead to predictable and unengaging gameplay.

    Multi-agent system for managing a game settlement with an expert-based behavior selection system for game characters · 2026 · DOI

  • The industry is facing a fundamental dichotomy between economic crisis and technological revolution. The adaptation of archaic cultural codes to the needs of a digital society is a key challenge.

    The Application of Artificial Intelligence Technologies and Novel Prospects for the Representation of Historical and Mythological Content in the U.S. Video Game Industry · 2026 · DOI

  • The need for a theoretical framework to understand how American developers adapt archaic cultural codes to the needs of a digital society. The lack of understanding of how generative AI can be used to create dynamic mythological content.

    The Application of Artificial Intelligence Technologies and Novel Prospects for the Representation of Historical and Mythological Content in the U.S. Video Game Industry · 2026 · DOI

  • From model-based reinforcement learning and video generation to embodied robotics and ultimately, physical AI, researchers across AI subfields are building systems that they call "world models", yet there is no consensus on what a world model fundamentally is, what it should predict, or how it should be built.

    A Definition and Roadmap for World Models · 2026

  • Prior work has focused on expert-level or even superhuman play, leaving a gap in the understanding of novice gameplay.

    People use fast and flat simulation to reason about new games · 2026 · DOI

  • The paper identifies a gap in the current understanding of GenAI, highlighting the need for a more nuanced approach. The paper argues that most analyses of GenAI are limited to two roles: a magical tool or a destructive tool.

    False dilemmas and real challenges: GenAI and the algorithmization of experience · 2026 · DOI

  • To explore the application of the approach to other domains. To investigate the use of neural network architectures in the system. To evaluate the system on other datasets and in different contexts.

    Computational and Machine Applications of a Narrative Theory Based Symbolic Ontology: Movie Search and Recommendation · 2026 · DOI

  • The paper aims to address the question of whether add-on software encroaches on the scope of protection of the game software.

    “Action Replay II” · 2026 · DOI

  • The PGN format is able to record all game moves and associated information about details such as the location, date and player names, but it is impractical for finding aggregate information about large number of games.

    Chess_db: A framework for working with large chess game datasets. · 2026 · DOI

  • Applying the methods to other board games with similar characteristics. Extending the research to four-player settings. Exploring other state encodings and algorithms to further improve performance.

    OPTIMIZING DEEP REINFORCEMENT LEARNING FOR BOARD GAMES: A COMPARATIVE STUDY OF DQN AND PPO ON LUDO WITH STRUCTURED STATE ENCODING · 2026 · DOI

  • A falta de estudos sobre a aplicação de IA em diálogos de NPCs em jogos. A necessidade de desenvolver abordagens mais eficientes para gerar diálogos de NPCs.

    A APLICAÇÃO DA INTELIGÊNCIA ARTIFICIAL EM DIÁLOGOS DE PERSONAGENS NÃO JOGÁVEIS EM UM JOGO DE RPG · 2026 · DOI

  • The development of automated scenario generation methodologies. The development of specialized algorithms tailored to HLSMAC's unique challenges.

    HLSMAC: A New StarCraft Multi-Agent Challenge for High-Level Strategic Decision-Making · 2026 · DOI

  • Integrating more principled causal discovery techniques or controlled interaction settings to bridge the gap between functional dependencies and verified causal mechanisms.

    SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model · 2026 · DOI

  • Further research can be done to apply the FFZNs-Frank model to other AI-powered narrative intelligence systems - The ability to propagate and monitor reliability throughout the DM process can be explored…

    A novel fermatean fuzzy Z-number FRANK-WASPAS model for evaluating AI-powered narrative intelligence systems · 2026 · DOI

  • The conventional MAGDM methods tend to deteriorate in case of inaccurate, partial, or reliability-sensitive data. The limitations of traditional WASPAS methods in handling uncertainty and ambiguity.

    A novel fermatean fuzzy Z-number FRANK-WASPAS model for evaluating AI-powered narrative intelligence systems · 2026 · DOI

Most-cited papers in Artificial Intelligence in Games

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Open questions raised by papers listed on this page include: (1) The lack of engagement and replayability in current mobile dungeon crawlers (“RISE OF SHADOWS: DEVELOPMENT OF A 2D ANDROID DUNGEON CRAWLER WITH AI DRIVEN…”, 2026); (2) There is a need for a more nuanced understanding of narrative comprehension and its role in media recommendation (“Computational and Machine Applications of a Narrative Theory Based Symbolic…”, 2026); (3) The paper identifies the challenge of scaling imperfect-information games due to the lack of a formal task model and evaluation metric for hand abstraction (“Beyond Outcome-Based Imperfect-Recall: Higher-Resolution Abstractions for…”, 2026); (4) The lack of variation in the Skinner box could produce results that are specific to a narrow set of conditions, thus giving rise to a failure to reproduce an effect when task characteristics change even modestly (“Video game engines as the new “virtual” Skinner box”, 2026); (5) The lack of a qualitative intellectual component in game characters can lead to predictable and unengaging gameplay (“Multi-agent system for managing a game settlement with an expert-based behavior…”, 2026). 107 gap statements have been mined from Artificial Intelligence in Games papers in our 4.5M-paper local library, which holds 647 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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