Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment最新文献_第3页

Story Shaping: Teaching Agents Human-Like Behavior with Stories 故事塑造:用故事教导代理类人行为

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27528

Xiangyu Peng, Christopher Cui, Wei Zhou, Renee Jia, Mark Riedl

{"title":"Story Shaping: Teaching Agents Human-Like Behavior with Stories","authors":"Xiangyu Peng, Christopher Cui, Wei Zhou, Renee Jia, Mark Riedl","doi":"10.1609/aiide.v19i1.27528","DOIUrl":"https://doi.org/10.1609/aiide.v19i1.27528","url":null,"abstract":"Reward design for reinforcement learning agents can be difficult in situations where one not only wants the agent to achieve some effect in the world but where one also cares about how that effect is achieved. For example, we might wish for an agent to adhere to a tacit understanding of commonsense, align itself to a preference for how to behave for purposes of safety, or taking on a particular role in an interactive game. Storytelling is a mode for communicating tacit procedural knowledge. We introduce a technique, Story Shaping, in which a reinforcement learning agent infers tacit knowledge from an exemplar story of how to accomplish a task and intrinsically rewards itself for performing actions that make its current environment adhere to that of the inferred story world. Specifically, Story Shaping infers a knowledge graph representation of the world state from observations, and also infers a knowledge graph from the exemplar story. An intrinsic reward is generated based on the similarity between the agent's inferred world state graph and the inferred story world graph. We conducted experiments in text-based games requiring commonsense reasoning and shaping the behaviors of agents as virtual game characters.","PeriodicalId":498041,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135303515","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}

引用次数: 0

Language as Reality: A Co-Creative Storytelling Game Experience in 1001 Nights Using Generative AI 语言即现实:《一千零一夜》中使用生成AI的合作故事叙述游戏体验

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27539

Yuqian Sun, Zhouyi Li, Ke Fang, Chang Hee Lee, Ali Asadipour

{"title":"Language as Reality: A Co-Creative Storytelling Game Experience in 1001 Nights Using Generative AI","authors":"Yuqian Sun, Zhouyi Li, Ke Fang, Chang Hee Lee, Ali Asadipour","doi":"10.1609/aiide.v19i1.27539","DOIUrl":"https://doi.org/10.1609/aiide.v19i1.27539","url":null,"abstract":"Generative AI (GenAI), encompassing image generation and large language models (LLMs), has opened new avenues for gameplay experiences. This paper introduces \"1001 Nights\", a narrative game centered on GenAI. Drawing inspiration from Wittgenstein's note, \"The limits of my language mean the limits of my world\", the game exemplifies the concept of language as reality. The protagonist, Shahrzad, possesses a unique power: specific keywords, such as \"sword\" or \"shield\", when spoken by others in tales, materialize as tangible weapons, serving as battle equipment against the King. Players guide the LLM-driven King in co-creating narratives, with GPT-4 employing LLM reasoning methods to ensure story consistency. As these narratives progress, the depicted world is dynamically generated and visualized through Stable Diffusion, blurring the boundaries between narrative and in-game reality. This fusion of interactive storytelling combines gameplay paradigms and story together with dynamic content generation. Players not only aim to alter Shahrzad's fate from the original folklore, but also leverage the power of natural language to shape the game's world. With this example, we propose the term \"AI-Native games\" to categorize innovative games where GenAI is fundamental to the game's novel mechanics and very existence.","PeriodicalId":498041,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135303518","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}

引用次数: 0

Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analitics 超越元:利用游戏设计参数进行补丁不可知的电子竞技分析

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27507

Alan Pedrassoli Chitayat, Florian Block, James Walker, Anders Drachen

{"title":"Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analitics","authors":"Alan Pedrassoli Chitayat, Florian Block, James Walker, Anders Drachen","doi":"10.1609/aiide.v19i1.27507","DOIUrl":"https://doi.org/10.1609/aiide.v19i1.27507","url":null,"abstract":"Esport games comprise a sizeable fraction of the global games market, and is the fastest growing segment in games. This has given rise to the domain of esports analytics, which uses telemetry data from games to inform players, coaches, broadcasters and other stakeholders. Compared to traditional sports, esport titles change rapidly, in terms of mechanics as well as rules. Due to these frequent changes to the parameters of the game, esport analytics models can have a short life-spam, a problem which is largely ignored within the literature. This paper extracts information from game design (i.e. patch notes) and utilises clustering techniques to propose a new form of character representation. As a case study, a neural network model is trained to predict the number of kills in a Dota 2 match utilising this novel character representation technique. The performance of this model is then evaluated against two distinct baselines, including conventional techniques. Not only did the model significantly outperform the baselines in terms of accuracy (85% AUC), but the model also maintains the accuracy in two newer iterations of the game that introduced one new character and a brand new character type. These changes introduced to the design of the game would typically break conventional techniques that are commonly used within the literature. Therefore, the proposed methodology for representing characters can increase the life-spam of machine learning models as well as contribute to a higher performance when compared to traditional techniques typically employed within the literature.","PeriodicalId":498041,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135303672","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}

引用次数: 0

Generally Genius: A Generals.io Agent Development and Data Collection Framework 天才:将军。io代理开发和数据收集框架

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27536

Aaditya Bhatia, Austin Davis, Soumik Ghosh, Gita Sukthankar

引用次数: 0

Understanding Human-AI Teaming Dynamics through Gaming Environments 通过游戏环境理解人类与ai的合作动态

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27541

Qiao Zhang

引用次数: 0

Herd’s Eye View: Improving Game AI Agent Learning with Collaborative Perception 羊群视角:利用协作感知改进游戏AI代理学习

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27526

Andrew Nash, Andrew Vardy, Dave Churchill

引用次数: 0

Probabilistic Logic Programming Semantics For Procedural Content Generation 面向过程内容生成的概率逻辑编程语义

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27525

Abdelrahman Madkour, Chris Martens, Steven Holtzen, Casper Harteveld, Stacy Marsella

引用次数: 0

Language Model-Based Player Goal Recognition in Open World Digital Games 基于语言模型的开放世界数字游戏玩家目标识别

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27503

Yeo Jin Kim, Alex Goslen, Jonathan Rowe, Bradford Mott, James Lester

{"title":"Language Model-Based Player Goal Recognition in Open World Digital Games","authors":"Yeo Jin Kim, Alex Goslen, Jonathan Rowe, Bradford Mott, James Lester","doi":"10.1609/aiide.v19i1.27503","DOIUrl":"https://doi.org/10.1609/aiide.v19i1.27503","url":null,"abstract":"Devising models that reliably recognize player goals is a key challenge in creating player-adaptive games. Player goal recognition is the task of automatically recognizing the intent of a player from a sequence of observed player actions in a game environment. In open-world digital games, players often undertake suboptimal and varied sequences of actions to achieve goals, and the high degree of freedom afforded to players makes it challenging to identify sequential patterns that lead toward specific goals. To address these issues, we present a player goal recognition framework that utilizes a fine-tuned T5 language model, which incorporates our novel attention mechanism called Temporal Contrary Attention (TCA). The T5 language model enables the framework to exploit correlations between observations through non-sequential self-attention within input sequences, while TCA enables the framework to learn to eliminate goal hypotheses by considering counterevidence within a temporal window. We evaluate our approach using game trace data collected from 144 players' interactions with an open-world educational game. Specifically, we investigate the predictive capacity of our approach to recognize player goals as well as player plans represented as abstract actions. Results show that our approach outperforms non-linguistic machine learning approaches as well as T5 without TCA. We discuss the implications of these findings for the design and development of player goal recognition models to create player-adaptive games.","PeriodicalId":498041,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135303673","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}

引用次数: 0

Utilizing Generative Adversarial Networks for Stable Structure Generation in Angry Birds 基于生成对抗网络的愤怒的小鸟稳定结构生成

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27496

Frederic Abraham, Matthew Stephenson

引用次数: 0

A Computational Tool for Recoloring Based on User Emotions 一种基于用户情绪的重着色计算工具

Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment Pub Date : 2023-10-06 DOI: 10.1609/aiide.v19i1.27531

Jungah Son, Marko Peljhan, George Legrady, Misha Sra

引用次数: 0