Towards Intelligent Interactive Theatre: Drama Management as a way of Handling Performance

In this paper, we present a new modality for intelligent interactive narratives within the theatre domain. We discuss the possibilities of using an intelligent agent that serves as a drama manager and as an actor that plays a character within the live theatre experience. We pose a set of research challenges that arise from our analysis towards the implementation of such an agent, as well as potential methodologies as a starting point to bridge the gaps between current literature and the proposed modality.Comment: International Conference on Interactive Digital Storytelling (ICIDS) 201

Exploring Apprenticeship Learning for Player Modelling in Interactive Narratives

In this paper we present an early Apprenticeship Learning approach to mimic the behaviour of different players in a short adaption of the interactive fiction Anchorhead. Our motivation is the need to understand and simulate player behaviour to create systems to aid the design and personalisation of Interactive Narratives (INs). INs are partially observable for the players and their goals are dynamic as a result. We used Receding Horizon IRL (RHIRL) to learn players' goals in the form of reward functions, and derive policies to imitate their behaviour. Our preliminary results suggest that RHIRL is able to learn action sequences to complete a game, and provided insights towards generating behaviour more similar to specific players.Comment: Extended Abstracts of the 2019 Annual Symposium on Computer-Human Interaction in Play (CHI Play

Directed Emergent Drama

A fully interactive drama, where the player interacts with intelligent Non- Player Characters (NPCs), can revolutionise entertainment, gaming, education, and therapy. Creating such a genuinely interactive drama that is entertaining and gives players a sense of coherency as active participants in the unfolding drama has seen a substantial research effort. Authors have the power to shape dramatised stories for theatre or television at will. Conversely, the authors' ability to shape interactive drama is limited because the drama emerges from players' and NPCs actions during game-play, which significantly limits authoring control. A coherent drama has a recognisable dramatic structure. One philosophy is to use planning algorithms and narrative structures to reduce required authoring. However, planning algorithms are intractable for the large state-spaces intrinsic to interactive dramas, and they have not reduced the authoring problem sufficiently. A more straightforward and computationally feasible method is emergent interactive drama from players' and NPCs' actions. The main difficulty with this approach is maintaining a drama structure and theme, such as a mystery theme or a training scenario, that the player experiences while interacting with the game world. Therefore, it is necessary to impose some form of structure to guide or direct the unfolding drama. The solution introduced in this thesis is to distribute the computation among autonomous actors that are guided by goals and drama structures which a centralised autonomous director agent distributes among the actors, which comprises the following four main elements: a) autonomous rational actor agents that know they are acting and can negotiate dialogues between them to remain realistic while simultaneously progressing the drama, without the player knowing, b) Bayesian network to model the actors reasoning, including beliefs about other actors' mental states c) an autonomous director agent uses "schemas", conceptual structures based on motifs, to guide the actors

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

DIEGESIS A multi-agent Digital Interactive Storytelling framework using planning and re-planning techniques

In recent years, the field of Digital Interactive Storytelling (DIS) has become very popular both in academic circles, as well as in the gaming industry, in which stories are becoming a unique selling point. Academic research on DIS focuses in the search for techniques that allow the creation of systems that can generate dynamically interesting stories which are not linear and can change dynamically at runtime as a consequence of a player’s actions, therefore leading to different story endings.To reach this goal, DIS systems usually employ Artificial Intelligence planning and re-planning algorithms as part of their solution. There is a lack of algorithms created specifically for DIS purposes since most DIS systems use generic algorithms, and they do not usually assess if and why a given algorithm is the best solution for their purposes. Additionally, there is no unified way (e.g. in the form of a selection of metrics) to evaluate such systems and algorithms.To address these issues and to provide new solutions to the DIS field, we performed a review of related DIS systems and algorithms, and based on the critical analysis of that work we designed and implemented a novel multi-agent DIS framework called DIEGESIS, which includes –among other novel aspects- two new DIS-focused planning and re-planning algorithms.To ensure that our framework and its algorithms have met the specifications we set, we created a large scale evaluation scenario which models the story of Troy, derived from Homer’s epic poem, “Iliad”, which we used to perform a number of evaluations based on metrics that we chose and we consider valuable for the DIS field. This collection of requirements and evaluations could be used in the future from other DIS systems as a unified test-bed for analysis and evaluation of such systems

An Evaluation of the Effects of the Coach-Athlete Relationship on Athlete Mental Health

There is a demand to target the mental health needs of collegiate athletes, who are considered to be at-risk for physiological injuries, psychological disturbances, and academic problems. Due to the dynamic nature of the coach-athlete relationship, assessing the impact coaches have on athletes’ psychological wellbeing is imperative to shift the way mental health is addressed within this population. The current study aims to address the relationship between perceived problems in the coach-athlete relationship and mental health of college students who participate in organized sport. I hypothesize that problems in the relationship have serious implications for athletes and mental health providers in that an athlete’s perception of problems in the coach-athlete relationship will predict more mental health problems, substance use, and stress than athletes who do not identify problems in the coach-athlete relationship. In addition, the current study aims to understand gender related differences in mental health complaints, substance use, and perception of problems within the coach-athlete relationship. I hypothesize that male and female athletes will report differences in their experience of these three domains

Friendly lords implementing an artificial intelligence social architecture in Mount& Blade II: Bannerlord

Despite living in a golden age for video games where there is an increase in the development and popularity of new technologies, such as Virtual Reality and Augmented Reality, and constant improvements being made on immersion, either through rich storytelling, high graphical fidelity or even gameplay itself, one area that is generally lacking on innovation is the social interaction of Non-Playable Characters. The credibility of these virtual characters (usually called NPCs) requires that they have human characteristics, such as emotions and the ability to think and make decisions depending on their own will. One of the most important characteristics is the ability to socialize and interact with each other. The main objective of this work was to implement a Social Architecture of Artificial Intel ligence in the game Mount&Blade II: Bannerlord to enhance the credibility of NPCs, making them socially more active and interesting, and improving the User Experience. In the game in which this study takes place (respectively Mount&Blade II: Bannerlord), although there are plenty of NPCs in the world, these are extremely limited, predictable and rarely demonstrate social behaviors. It also addresses some socio-emotional architectures such as CiF and FAtiMA. While FA tiMA is more focused on the generation of emotions, and how those emotions may affect the behaviour of characters, CiF has an explicit representation of social relations between NPCs and how the can influence behaviour. Due to this, the system architecture used as the basis for our model is the CiF architecture, also used before in some popular games like Skyrim and Conan Exiles. It is a system designed to be able to generate social behavior for the social agents, in this case the virtual characters. Instead of looking static and appearing to be clones of each other, the NPCs will appear more natural, making them more interesting and believable from the point of view of social interaction. One of the major differences between the CiF model and the developed model, named Comme il Faut - Bannerlord (CiF-BL), was, respectively, an addition of a centralized component, which will manage about which NPCs will be able to engage in interactions, how many Social Interactions will be able to take place at the same time, when these are started and finished From CiF-BL’s perspective, the player is just another character, and just as NPCs will want to interact with each other, they will also want to interact with the player. To do this work, it was necessary to adapt the game’s existing dialog system to make CiF BL’s changes possible. Adding the options that allow the player to interact socially with an NPC and vice-versa. It was also necessary to adapt and implement another game system, responsible for signaling and informing the most relevant locations and characters. This adaptation was responsible for making it possible to visualize the interactions between the different NPCs. Thus, during the time that the user is present in the virtual world, the virtual characters will no longer have a totally irrelevant and figurative role in the game, and will have a greater social participation. With the goal of appearing more believable, natural, and, to look more like "living beings". The developed model was validated and evaluated through user tests. Unfortunately, due to COVID-19 restrictions that occurred during the execution of this thesis, it was not possible to conduct a controlled in-person evaluation (which would be the ideal way to evaluate our work). Instead, a mod was produced and released online to the Bannerlords player and modding community. The only difference between the mod and the base version of the game was the CIF-BL model used to control the NPCs. The mod was called "Friendly Lords" and released in 18th of August 2021, both in NexusMods and in ModDB. The mod was announced on social networks, such as Reddit, in groups that were related to the game. Participants were voluntarily invited to complete an anonymous questionnaire regarding their gaming experience, and the answers were collected. From the analysis of these same answers, very favorable results were obtained for the objectives we defined. However, overall, the feedback from players and the community has been very positive about the mod and its modifications to the game. Some examples are that it looks promising, that they want active development, and that are grateful to help bring new life to the game. People give suggestions and constructive feedback to implement in the mod and help get a better experience. Meanwhile, some players have shown more interest and offered to collaborate directly in the development, either for more dialogue options between the NPCs, or to translate the mod respectively into Turkish which is the native language of the studio currently developing the game. In short, using the social architecture implemented in the game, the Credibility of NPCs and the Social Presence improved by more than 30%, having successfully achieved the goals. This document describes in more detail the process of researching, implementing and testing the model. To improve this work and the Artificial Intelligence social architecture, it would be necessary to at least add more personality traits and a greater number of different social interactions, for the NPCs to have a greater diversity in terms of their social behavior.Apesar de vivermos numa era dourada para os videojogos onde há um aumento do desen volvimento e da popularidade de novas tecnologias, como a Realidade Virtual e a Realidade Aumentada, e constantes melhorias a serem feitas na imersão, seja através de ricas narrativas, fidelidade gráfica elevada ou até mesmo gameplay em si, uma área que geralmente não é alvo de inovação é a interação social entre as Personagens Não Jogáveis. A credibilidade dessas personagens virtuais (normalmente chamadas de NPCs) exige que estas tenham características humanas, como emoções e a capacidade de pensar e tomar decisões dependendo da sua própria vontade. Uma das características mais importante é a capacidade de socializar e interagir uns com os outros. O objectivo principal deste trabalho é implementar uma Arquitectura Social de Inteligência Artificial no jogo Mount&Blade II: Bannerlord para incrementar a Credibilidade dos NPCs, tornando-os socialmente mais ativos e interessantes, e melhorar a Experiência do Utilizador. No jogo em que se realiza este estudo (respetivamente Mount&Blade II: Bannerlord), embora haja uma abundância de NPCs no mundo, estes são extremamente limitados, previsíveis e raramente demonstram comportamentos sociais. Este trabalho aborda diferentes arquitecturas socio-emocionais, como Comme il Faut (CiF) e FAtiMA. Enquanto FAtiMA está mais centrado na geração de emoções, e como essas emoções podem afectar o comportamento das personagens, CiF tem uma representação explícita das relações sociais entre os NPCs e de que forma o comportamento pode influenciar. Devido a isto, a arquitetura do sistema usada como base para o nosso modelo é a arquitetura CiF, também já usada antes em alguns jogos populares como Skyrim e Conan Exiles. É um sistema concebido para ser capaz de gerar comportamentos sociais para os agentes sociais, neste caso, os personagens virtuais. Em vez de parecerem estáticos e aparentarem serem clones uns dos outros, os NPCs vão parecer mais naturais, tornando-os mais interessantes e credíveis do ponto de vista da interação social. Uma das maiores diferenças entre o modelo CiF e o modelo final desenvolvido, nomeado de Comme il Faut - Bannerlord (CiF-BL), foi, respectivamente, uma adição de um componente centralizado, que irá fazer a gestão acerca de quais os NPCs que estarão aptos para se envolverem em interações, quantas Interações Sociais serão capazes de se realizar ao mesmo tempo, quando estas são iniciadas e terminadas. Da perspectiva do CiF-BL, o jogador é apenas uma outra personagem e, assim como os NPCs vão querer interagir uns com os outros, eles também vão querer interagir com o jogador. Para realizar este trabalho, foi necessário adaptar o atual sistema de diálogo já existente do jogo para possibilitar as alterações do CiF-BL. Adicionando assim as opções que permitem ao jogador interagir socialmente com um NPC e vice-versa. Foi necessária também uma adaptação e a implementação de um outro sistema do jogo, responsável por assinalar e informar as localizações e os personagens mais relevantes. Esta adaptação foi responsável para tornar possível a visualização das interações entre os diferentes NPCs. Assim, durante o tempo em que o utilizador estiver presente no mundo virtual, as personagens virtuais irão deixar de ter um papel totalmente irrelevante e figurativo no jogo, e, terão uma maior participação social. Com o objectivo de parecerem mais credíveis, naturais, e, de se assemelharem mais com “seres vivos”. Para a validação e a avaliação do modelo, este foi sujeito a testes de utilizador. Infelizmente, devido às restrições COVID-19 que ocorreram durante a execução desta tese, não foi possível realizar uma avaliação controlada presencialmente (que seria a forma ideal de avaliar o nosso trabalho). Em vez disso, um mod foi produzido e lançado online para os jogadores do jogo Bannerlord e para a comunidade modding. A única diferença entre o mod e a versão base do jogo foi o modelo CIF-BL usado para controlar e melhorar os NPCs. O mod foi chamado de "Friendly Lords" e lançado em 18 de agosto de 2021, tanto no site NexusMods como no ModDB. O mod foi anunciado nas redes sociais, como o Reddit, em grupos que estavam relacionados com o jogo. Os participantes foram convidados voluntariamente a preencher um questionário anónimo relativamente à sua experiência de jogo, sendo feita a recolha das respostas. A partir da análise dessas mesmas respostas, foram obtidos resultados muito favoráveis para os objectivos que definimos. Entretanto, no geral, o feedback dos jogadores e da comunidade foi muito positivo sobre o mod e sobre as suas modificações no jogo. Alguns exemplos são que parece promissor, que querem um desenvolvimento ativo, e que estão gratos por ajudar a trazer uma nova vida ao jogo. As pessoas dão sugestões e feedback construtivo para implementar no mod e ajudar a obter uma melhor experiência. Entretanto, alguns jogadores mostraram mais interesse e disponibilizaram se para colaborar diretamente no desenvolvimento, quer seja para mais opções de diálogos entre os NPCs, quer seja para a tradução do mod, respectivamente para Turco que é a língua materna do estúdio que atualmente desenvolve o jogo. Resumindo, usando a arquitetura social implementada no jogo, a Credibilidade dos NPCs e a qualidade do comportamento social melhorou mais de 30%, tendo atingido com sucesso os objetivos. Este documento descreve mais em pormenor o processo de pesquisa, de implemen tação e de teste do modelo. Para melhorar este trabalho e a sua arquitetura social de Inteligência Artificial, seria necessário, pelo menos, adicionar mais traços de personalidade e um maior número de diferentes interações sociais, para os NPCs terem uma maior diversidade quanto ao seu comportamento social

Collaborative narrative generation in persistent virtual environments

This thesis describes a multi-agent approach to generating narrative based on the activities of participants in large-scale persistent virtual environments, such as massivelymultiplayer online role-playing games (MMORPGs). These environments provide diverse interactive experiences for large numbers of simultaneous participants. Involving such participants in an overarching narrative experience has presented challenges due to the difficulty of incorporating the individual actions of so many participants into a single coherent storyline. Various approaches have been adopted in an attempt to solve this problem, such as guiding players to follow pre-designed storylines, or giving them goals to achieve that advance the storyline, or by having developers (‘dungeon masters’) adapt the narrative to the real-time actions of players. However these solutions can be inflexible, and/or fail to take player interaction into account, or do so only at the collective level, for groups of players. This thesis describes a different approach, in which embodied witness-narrator agents observe participants’ actions in a persistent virtual environment and generate narrative from reports of those actions. The generated narrative may be published to external audiences, e.g., via community websites, Internet chatrooms, or SMS text messages, or fed back into the environment in real-time to embellish and enhance the ongoing experience with new narrative elements derived from participants’ own achievements. The design and implementation of this framework is described in detail, and compared to related work. Results of evaluating the framework, both technically, and through a live study, are presented and discussed