Michal Bída

Pogamut 3 Can Assist Developers in Building AI (Not Only) for Their Videogame Agents

Many research projects oriented on control mechanisms of virtual agents in videogames have emerged in recent years. However, this boost has not been accompanied with the emergence of toolkits supporting development of these projects, slowing down the progress in the field. Here, we present Pogamut 3, an open source platform for rapid development of behaviour for virtual agents embodied in a 3D environment of the Unreal Tournament 2004 videogame. Pogamut 3 is designed to support research as well as educational projects. The paper also briefly touches extensions of Pogamut 3; the ACT-R integration, the emotional model ALMA integration, support for control of avatars at the level of gestures, and a toolkit for developing educational scenarios concerning orientation in urban areas. These extensions make Pogamut 3 applicable beyond the domain of computer games.

Towards Fast Prototyping of IVAs Behavior: Pogamut 2

We present the platform for IVAs development in the human like environment of the first-person shooter game Unreal Tournament 2004. This environment is extendible and supported by vast community of users. Based on our previous experience the problem of fast verification of models of artificial intelligence or IVAs is in implementation issues. The developer spends most of his time solving technical environment dependent issues and malfunctions, which drives him away from his goals. Therefore our modular platform provides a tool, which helps solving those problems and the developer can spend saved time by solving another AI based issues and model verification. The platform is aimed for research and educational purposes.

Emohawk: Searching for a Good Emergent Narrative

We report on the progress we have achieved in development of Emohawk, a 3D virtual reality application with an emergent narrative for teaching high-school students and undergraduates the basics of virtual characters control, emotion modelling, and narrative generation. Besides, we present a new methodology, used in Emohawk, for purposeful authoring of emergent narratives of Facades complexity. The methodology is based on massive automatic search for stories that are appealing to the audience whilst forbidding the unappealing ones during the design phase.

Learning and Game AI

The incorporation of learning into commercial games can enrich the player experience, but may concern developers in terms of issues such as losing control of their game world. We explore a number of applied research and some fielded applications that point to the tremendous possibilities of machine learning research including game genres such as real-time strategy games, flight simulation games, car and motorcycle racing games, board games such as Go, an even traditional game-theoretic problems such as the prisoners dilemma. A common trait of these works is the potential of machine learning to reduce the burden of game developers. However a number of challenges exists that hinder the use of machine learning more broadly. We discuss some of these challenges while at the same time exploring opportunities for a wide use of machine learning in games.

When a couple goes together: walk along steering

Steering techniques are widely used for navigation of single agents or crowds and flocks. Steerings also have the potential to coordinate movement of human-like agents in very small groups so that the resulting behavior appears socially believable, but this dimension is less explored. Here, we present one such “social” steering, the Walk Along steering for navigating a couple of agents to reach a certain place together. The results of a believability study with 26 human subjects who compared the new steering to the known Leader Following steering in eight different scenarios suggest the superiority of the Walk Along steering in social situations.

3D Immersion in Virtual Agents Education

Many projects featuring intelligent virtual agents have emerged in last years, but not many reports on their advances in education. This paper presents the curricula of a university course on Modelling Behaviour of Human and Animal-like Agents, including a seminar in which students develop their own virtual agents using a toolkit we have developed. This course has been also scaled for a workshop with computer science high-school students. An evaluation of the course is presented and main lessons learned overviewed. The paper also explicitly formulates the teaching methodology underpinning the course and outlines several general questions hoping to start a broader discussion on educational issues related to the field of intelligent virtual agents.

Search in Real-Time Video Games

This chapter arises from the discussions of an experienced international group of researchers interested in the potential for creative application of algorithms for searching finite discrete graphs, which have been highly successful in a wide range of application areas, to address a broad range of problems arising in video games. The chapter first summarises the state of the art in search algorithms for games. It then considers the challenges in implementing these algorithms in video games (particularly real time strategy and first-person games) and ways of creating searchable discrete representations of video game decisions (for example as state-action graphs). Finally the chapter looks forward to promising techniques which might bring some of the success achieved in games such as Go and Chess, to real-time video games. For simplicity, we will consider primarily the objective of maximising playing strength, and consider games where this is a challenging task, which results in interesting gameplay.

Towards Automatic Story Clustering for Interactive Narrative Authoring

Interactive storytelling systems are capable of producing many variants of stories. A major challenge in designing storytelling systems is the evaluation of the resulting narrative. Ideally every variant of the resulting story should be seen and evaluated, but due to combinatorial explosion of the story space, this is unfeasible in all but the smallest domains. However, the system designer still needs to have control over the generated stories and his input cannot be replaced by a computer. In this paper we propose a general methodology for semi-automatic evaluation of narrative systems based on tension curve extraction and clustering of similar stories. Our preliminary results indicate that a straightforward approach works well in simple scenarios, but for complex story spaces further improvements are necessary.

To date or not to date? a minimalist affect-modulated control architecture for dating virtual characters

As part of our broader initiative on promoting the education in the field of IVA control mechanisms at high schools and universities, we have created a micro-game Cinema Date, which introduces students challenges posed by controlling 3D virtual characters and expressing their emotional state. The game features two virtual teenagers dating on their way to the cinema. The player can influence the course of the date by influencing behavior of the boy. Existing IVA architectures did not satisfy our requirements on the architecture being reasonably simple, yet capturing affect-modulated behavior, transition behavior and future-directed intentions. Here, we present the game, focusing on the minimalist control architecture of its main characters.

Extensions and Applications of Pogamut 3 Platform

We present recent extensions for the intelligent virtual agent development platform Pogamut 3. These extensions are: the agent coordination language StorySpeak designed for the purposes of storytelling applications, support for gestures based on BML, the visual editor of reactive plans, connection of the cognitive architecture ACT-R, an educational application aimed at orientation in urban areas and finally an emotional model.