Magy Seif El-Nasr

Learning through game modding

There has been a recent increase in the number of game environments or engines that allow users to customize their gaming experiences by building and expanding game behavior. This article describes the use of modifying, or modding, existing games as a means to learn computer science, mathematics, physics, and aesthetic principles. We describe two exploratory case studies of game modding in classroom settings to illustrate skills learned by students as a result of modding existing games. We also discuss the benefits of learning computer sciences skills (e.g., 3D graphics/mathematics, event-based programming, software engineering, etc.) through large design projects and how game design motivates students to acquire and apply these skills. We describe our use of multiple game modding environments in our classes. In addition, we describe how different engines can be used to focus students on the acquisition of particular skills and concepts.

Emotionally expressive agents

The ability to express emotions is important for creating believable interactive characters. To simulate emotional expressions in an interactive environment, an intelligent agent needs both an adaptive model for generating believable responses, and a visualization model for mapping emotions into facial expressions. Recent advances in intelligent agents and in facial modeling have produced effective algorithms for these tasks independently. We describe a method for integrating these algorithms to create an interactive simulation of an agent that produces appropriate facial expressions in a dynamic environment. Our approach to combining a model of emotions with a facial model represents a first step towards developing the technology of a truly believable interactive agent which has a wide range of applications from designing intelligent training systems to video games and animation tools.

Game Analytics: Maximizing the Value of Player Data

Developing a successful game in todays market is a challenging endeavor. Thousands of titles are published yearly, all competing for players time and attention. Game analytics has emerged in the past few years as one of the main resources for ensuring game quality, maximizing success, understanding player behavior and enhancing the quality of the player experience. It has led to a paradigm shift in the development and design strategies of digital games, bringing data-driven intelligence practices into the fray for informing decision making at operational, tactical and strategic levels. Game Analytics - Maximizing the Value of Player Data is the first book on the topic of game analytics; the process of discovering and communicating patterns in data towards evaluating and driving action, improving performance and solving problems in game development and game research. Written by over 50 international experts from industry and research, it covers a comprehensive range of topics across more than 30 chapters, providing an in-depth discussion of game analytics and its practical applications. Topics covered include monetization strategies, design of telemetry systems, analytics for iterative production, game data mining and big data in game development, spatial analytics, visualization and reporting of analysis, player behavior analysis, quantitative user testing and game user research. This state-of-the-art volume is an essential source of reference for game developers and researchers. Key takeaways include: Thorough introduction to game analytics; covering analytics applied to data on players, processes and performance throughout the game lifecycle.In-depth coverage and advice on setting up analytics systems and developing good practices for integrating analytics in game-development and -management.Contributions by leading researchers and experienced professionals from the industry, including Ubisoft, Sony, EA, Bioware, Square Enix, THQ, Volition, and PlayableGames. Interviews with experienced industry professionals on how they use analytics to create hit games.

Understanding and evaluating cooperative games

Cooperative design has been an integral part of many games. With the success of games like Left4Dead, many game designers and producers are currently exploring the addition of cooperative patterns within their games. Unfortunately, very little research investigated cooperative patterns or methods to evaluate them. In this paper, we present a set of cooperative patterns identified based on analysis of fourteen cooperative games. Additionally, we propose Cooperative Performance Metrics (CPM). To evaluate the use of these CPMs, we ran a study with a total of 60 participants, grouped in 2-3 participants per session. Participants were asked to play four cooperative games (Rock Band 2, Lego Star Wars, Kameo, and Little Big Planet). Videos of the play sessions were annotated using the CPMs, which were then mapped to cooperative patterns that caused them. Results, validated through inter-rater agreement, identify several effective cooperative patterns and lessons for future cooperative game designs.

PETEEI: a PET with evolving emotional intelligence

The emergence of, what is now called, ‘emotional intellige nce’ has revealed yet another aspect of human intelligence. Emot ions were shown to have a major impact on many of our everyday tasks, including decision-making, planning, communication, and behavior. Researchers have recently acknowledged this major role that emotions play, and thus we see a variety of models bei ng presented on simulating emotions in agents. However, emotion is not a simple process, it is often linked with many other pr ocesses, one of which is learning. As it has long been emphasized throug h psychology literature, memory and experience help shape and build the dynamic nature of the emotional process. In this pa per, we introduce PETEEI (a PET with Evolving Emotional Intelligence). PETEEI is a general model for simulating emotions in agents, with a particular emphasis on incorporating vario us learning mechanisms so that it can produce emotions accor ding to its own experience. Furthermore, it was modeled to recogniz e and cope with the various mood and emotional changes of its owne r. We have implemented PETEEI using fuzzy logic. An evaluation involving twenty-one subjects indicated that simulating the dynamic emotional process through learning provides a significantly more believable agent.

Game Analytics – The Basics

Developing a profitable game in today’s market is a challenging endeavor. Thousands of commercial titles are published yearly, across a number of hardware platforms and distribution channels, all competing for players’ time and attention, and the game industry is decidedly competitive. In order to effectively develop games, a variety of tools and techniques from e.g. business practices, project management to user testing have been developed in the game industry, or adopted and adapted from other IT sectors. One of these methods is analytics, which in recent years has decidedly impacted on the game industry and game research environment.

Experiencing the reading glove

In this paper we describe the Reading Glove, a wearable RFID reader for interacting with a tangible narrative. Based on interviews with study participants, we present a set of observed themes for understanding how the wearable and tangible aspects of the Reading Glove influence the user experience. We connect our observational themes to theoretical notions from interactive narrative and tangible interaction to create a set of design considerations such as enacting a role, ownership and permission, multiplicity of interpretations and boundary objects.

Dynamic Intelligent Lighting for Directing Visual Attention in Interactive 3-D Scenes

Recent enhancements in real-time graphics have facilitated the design of high fidelity game environments with complex 3-D worlds inhabited by animated characters. Under such settings, it is hard, especially for the untrained eyes, to attend to an object of interest. Neuroscience research as well as film and theatre practice identified several visual properties, such as contrast, orientation, and color that play a major role in channeling attention. In this paper, we discuss an adaptive lighting design system called adaptive lighting for visual attention (ALVA) that dynamically adjusts the lighting color and brightness to enhance visual attention within game environments using features identified by neuroscience, psychophysics, and visual design literature. We also discuss some preliminary results showing the utility of ALVA in directing players attention to important elements in a fast paced 3-D game, and thus enhancing the game experience especially for nongamers who are not visually trained to spot objects or characters in such complex 3-D worlds.

Experiencing interactive narrative: A qualitative analysis of Façade

Abstract The topic of interactive narrative has been under research for many years. While there is research exploring the development of new algorithms that enable and enhance interactive narratives, few research projects focused on the question of how users interpret and experience an interactive narrative. In this paper we specifically focus on a single user interactive narrative experience since most work within this area focused on technological advancement and less on measurements of participants’ experiences. Taking this angle, we aim to report on an in-depth qualitative content analysis study, specifically analyzing users’ interpretations, emotions, and behavioral responses to an interactive narrative called Facade . We analyzed user data, including interviews and action logs, which include dialog uttered between participants and characters that inhabit Facade . Results from this analysis are discussed in the paper along with the methodology used and its limitations. These findings uncover several useful lessons that can help guide the design of future single user interactive narratives similar to Facade .

System for Automated Interactive Lighting (SAIL)

Successful lighting in video games is more than a physically accurate illumination model. Aesthetics and function are of equal or greater importance. Lighting designers may deviate from physical accuracy to help a player identify an important object or to more powerfully evoke a desired emotion. Under the assumption that fulfilling the pipeline needs of interactive lighting design requires more than solving the computer rendering equation, we set out to develop a System for Automated Interactive Lighting (SAIL). The goal for SAIL was to develop an adaptive system that maintains lighting design goals (aesthetic and functional) in the context of unpredictable, interactive experiences. This paper presents SAIL and the results of a qualitative evaluation of SAILs contributions. We describe the algorithms of SAIL, where it succeeds, and where it fails. We conclude with a plan for future work.