Bringing Stories Alive: Generating Interactive Fiction Worlds

World building forms the foundation of any task that requires narrative intelligence. In this work, we focus on procedurally generating interactive fiction worlds---text-based worlds that players "see" and "talk to" using natural language. Generating these worlds requires referencing everyday and thematic commonsense priors in addition to being semantically consistent, interesting, and coherent throughout. Using existing story plots as inspiration, we present a method that first extracts a partial knowledge graph encoding basic information regarding world structure such as locations and objects. This knowledge graph is then automatically completed utilizing thematic knowledge and used to guide a neural language generation model that fleshes out the rest of the world. We perform human participant-based evaluations, testing our neural model's ability to extract and fill-in a knowledge graph and to generate language conditioned on it against rule-based and human-made baselines. Our code is available at https://github.com/rajammanabrolu/WorldGeneration

Making Maps Available for Play: Analyzing the Design of Game Cartography Interfaces.

Maps in video games have grown into complex interactive systems alongside video games themselves. What map systems have done and currently do have not been cataloged or evaluated. We trace the history of game map interfaces from their paper-based inspiration to their current smart phone-like appearance. Read- only map interfaces enable players to consume maps, which is sufficient for wayfinding. Game cartography interfaces enable players to persistently modify maps, expanding the range of activity to support planning and coordination. We employ thematic analysis on game cartography interfaces, contributing a near-exhaustive catalog of games featuring such interfaces, a set of properties to describe and design such interfaces, a collection of play activities that relate to cartography, and a framework to identify what properties promote the activities. We expect that designers will find the contributions enable them to promote desired play experiences through game map interface design

Are NLP Models Good at Tracing Thoughts: An Overview of Narrative Understanding

Narrative understanding involves capturing the author's cognitive processes, providing insights into their knowledge, intentions, beliefs, and desires. Although large language models (LLMs) excel in generating grammatically coherent text, their ability to comprehend the author's thoughts remains uncertain. This limitation hinders the practical applications of narrative understanding. In this paper, we conduct a comprehensive survey of narrative understanding tasks, thoroughly examining their key features, definitions, taxonomy, associated datasets, training objectives, evaluation metrics, and limitations. Furthermore, we explore the potential of expanding the capabilities of modularized LLMs to address novel narrative understanding tasks. By framing narrative understanding as the retrieval of the author's imaginative cues that outline the narrative structure, our study introduces a fresh perspective on enhancing narrative comprehension

Interactive Concept of Operations Narrative Simulators

This paper reports on an exploratory design and development project. Specifically this paper discusses the design and development of Interactive Concept of Operations Narrative Simulators (ICONS) as a means of enhancing the functionality of traditional Concept of Operations documents by leveraging the affordances provided by applications commonly used within the Interactive Fiction literary genre. Recommendations for an ICONS design and development methodology, along a detailed description of a practical proof-of-concept ICONS created using this approach are discussed. The report concludes with a discussion of how ICONS can be extended to the K-12 mathematics education domain and conclude with a discussion of how ICONS can be used to assist those involved with strategic planning at Marshall Space Flight Center

Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark

Artificial agents have traditionally been trained to maximize reward, which may incentivize power-seeking and deception, analogous to how next-token prediction in language models (LMs) may incentivize toxicity. So do agents naturally learn to be Machiavellian? And how do we measure these behaviors in general-purpose models such as GPT-4? Towards answering these questions, we introduce MACHIAVELLI, a benchmark of 134 Choose-Your-Own-Adventure games containing over half a million rich, diverse scenarios that center on social decision-making. Scenario labeling is automated with LMs, which are more performant than human annotators. We mathematize dozens of harmful behaviors and use our annotations to evaluate agents' tendencies to be power-seeking, cause disutility, and commit ethical violations. We observe some tension between maximizing reward and behaving ethically. To improve this trade-off, we investigate LM-based methods to steer agents' towards less harmful behaviors. Our results show that agents can both act competently and morally, so concrete progress can currently be made in machine ethics--designing agents that are Pareto improvements in both safety and capabilities.Comment: ICML 2023 Oral; 31 pages, 5 figure

A Content Analysis Of The Developmental Bibliotherapeutic Implications Of The Books Nominated For The California Young Reader Medal (1975--1986)

Purpose. The purpose of this study was to investigate the developmental bibliotherapeutic implications of the California Young Reader Medal nominated books from 1975-1986 in six different selected categories of thematic content. Emotional Health, Self-Awareness, and Identity Needs; Cultural Differences; Family Relationships and Dynamics; Peer Relationships and Dynamics; Physical Limitations and Handicaps; and Economic Situations and Factors. Findings. Primary Category books, largely modern fanciful fiction, demonstrated limited developmental bibliotherapeutic potential. However, story illustrations affected the over-all impact of the story. Intermediate Category books had greater levels of potential, especially stories dealing with family, peers, and emotional health. The greatest levels of potential were present in the contemporary realistic fiction genre and in historical fiction. Intermediate Category books from the 1980s were higher in potential than books of the 1970s. Little distinction was found between the Primary Category books of the 70s and the 80s. Similar elements of story potential were identified by all groups, although at varying levels of sophistication. Many of the California titles had regional and national appeal. Recommendations. Based on the findings of this study, the major recommendations are as follows: (1) Developmental bibliotherapy as an art should be used in the study of literature with young children. Educators need to have an awareness of current issues confronting children and how these issues are treated in current literature. (2) Authors and publishers should produce quality books dealing with cultural differences and universal understanding as well as meaningful books in the genre of contemporary realistic fiction and historical fiction. Consideration should also be given to promoting books dealing with physical limitations and handicaps. (3) Teachers and librarians should continue the oral tradition of shared literature with children to enhance a child\u27s understanding and appreciation of the beauty of words, writing styles, cultural differences, and changing life situations. (4) State young reader program committees, librarians, and educators should identify quality books for inclusion on their masterlists to be read by children. (5) More content analysis studies, similar to this study, should be conducted to enrich the body of knowledge about children\u27s literature and to extend the understanding of the current thematic trends present in literature for the younger readers. (Abstract shortened with permission of author.

Practical AI Value Alignment Using Stories

As more machine learning agents interact with humans, it is increasingly a prospect that an agent trained to perform a task optimally - using only a measure of task performance as feedback--can violate societal norms for acceptable behavior or cause harm. Consequently, it becomes necessary to prioritize task performance and ensure that AI actions do not have detrimental effects. Value alignment is a property of intelligent agents, wherein they solely pursue goals and activities that are non-harmful and beneficial to humans. Current approaches to value alignment largely depend on imitation learning or learning from demonstration methods. However, the dynamic nature of values makes it difficult to learn values through imitation learning-based approaches. To overcome the limitations of imitation learning-based approaches, in this work, we introduced a complementary technique in which a value-aligned prior is learned from naturally occurring stories that embody societal norms. This value-aligned prior can detect the normative and non-normative behavior of human society as well as describe the underlying social norms associated with these behaviors. To train our models, we sourced data from the children’s educational comic strip, Goofus \& Gallant. Additionally, we have built another dataset by utilizing a crowdsourcing platform. This dataset was created specifically to identify the norms or principles exhibited in the actions depicted within the comic strips. To build a normative prior model, we trained multiple machine learning models to classify natural language descriptions and visual demonstrations of situations found in the comic strip as either normative or non-normative and into different social norms. Finally, to train a value-aligned agent, we introduced a reinforcement learning-based method, in which we train an agent with two reward signals: a standard task performance reward plus a normative behavior reward. The test environment provides the standard task performance reward, while the normative behavior reward is derived from the value-aligned prior model. We show how variations on a policy shaping technique can balance these two sources of reward and produce policies that are both effective and perceived as being more normative. We test our value-alignment technique on different interactive text-based worlds; each world is designed specifically to challenge agents with a task as well as provide opportunities to deviate from the task to engage in normative and/or altruistic behavior

Female Pleasure and Theories of Desire in Narrative Structure: Evolution, Futurity, and Species Survival in the Post-Human and Science Fiction Imaginary

This dissertation explores the complex relationship between an expanded narratological theory of narrative desire, inseparable in its relation to evolution and biological reproduction, and the future survival of humanity imagined across the narrative structures of three 21st-century works of dystopian science fiction. By examining the genre\u27s potential to address species survival specifically through female forms of desire identified as narrative recurrence, prolonged duration, and emotional resolution, this study concurrently develops a metatextual methodology that cultivates the overlooked liminal space of quiescence. This analytical framework emphasizes narrative structure over theme-based analysis to unlock the radical imagination present in the texts by highlighting the challenges of narrativizing a post-human future in Battlestar Galactica, Mass Effect 3, and Octavia Butler\u27s Parable of the Trickster. The reimagined television series Battlestar Galactica self-consciously poses questions regarding its own structural design. A moment of quiescence, positioned after the end and before the beginning of a narrative cycle in the epilogue, exists as a phase of unlimited potentiality beyond the activity of the diegetic text. In Mass Effect 3, the third installment of the massively successful video game franchise, the protests of dissatisfied gamers resulted in the creation of new ending options, revealing how quiescence can also be understood as the space surrounding the text as paratextual elements, existing adjacent to but separate from the main text, that directly influence interpretation and meaning. Finally, the archival materials of the unfinished book Parable of the Trickster, held at the Huntington Library and written by acclaimed science fiction author Octavia Butler, offers insights into quiescence as a location that exists akin to this pre-textual space. The archives reveal Butler’s struggle with severe writer’s block as a testament to the challenges and foreboding nature of envisioning humanity\u27s future as it pertains to evolution and species survival. By incorporating female sexuality into narrative desire, I propose that reviving this theory may offer value in contemporary structural analysis of plots, especially since the concept of quiescence allows us to explore aspects beyond the confines of the diegetic text in a world where narrative is becoming ever more interactive, multi-modal, intertextual, and transmedial. Science fiction during this era of convergence is also seeing a rapid transformation. As humanity increasingly faces existential threats such as artificial intelligence, pandemics, climate change, and nuclear apocalypse, innovative strategies and skills for survival must be developed that transcend our anthropocentric limitations. Although human reproduction is traditionally based on biological foundations that involve erotic desire, the reality of human survival - and reproduction - is rapidly evolving. The development of non-erotic desires such as scientific literacy, global cooperation, and ethical reasoning will become increasingly essential for species survival and, as this occurs, alterations to our human biology may fundamentally reshape our narrative constructs and forms of narrative desire. Ultimately, these texts reveal attempts at post-human forms of relationality within a genre of possibilities that self-consciously struggles to answer what form human survival may take in the future