Learning Human Behavior From Observation For Gaming Applications

The gaming industry has reached a point where improving graphics has only a small effect on how much a player will enjoy a game. One focus has turned to adding more humanlike characteristics into computer game agents. Machine learning techniques are being used scarcely in games, although they do offer powerful means for creating humanlike behaviors in agents. The first person shooter (FPS), Quake 2, is an open source game that offers a multi-agent environment to create game agents (bots) in. This work attempts to combine neural networks with a modeling paradigm known as context based reasoning (CxBR) to create a contextual game observation (CONGO) system that produces Quake 2 agents that behave as a human player trains them to act. A default level of intelligence is instilled into the bots through contextual scripts to prevent the bot from being trained to be completely useless. The results show that the humanness and entertainment value as compared to a traditional scripted bot have improved, although, CONGO bots usually ranked only slightly above a novice skill level. Overall, CONGO is a technique that offers the gaming community a mode of game play that has promising entertainment value

Frontline Employees’ Informal Learning and Customer Relationship Skills in Macao Casinos: An Empirical Study

This study uses qualitative methods to better understand how the informal learning of frontline employees influenced their customer relationship skills in dealing with patrons at gaming tables, in the hope of achieving positive customer experiences in a competitive environment in Macao. As casino operators need to get their employees to work after limited formal training, they might find that their emphasis on formal training might be insufficient to provide patrons with customized service in Macao. In this context, the concept of informal learning, which is determined and directed by learners themselves to further improve what they have learned from their formal training, is likely to be of special significance in Macao. Based upon a constructivistic framework, this study used semi-structured interviews to gather data from 49 frontline employees. The study relied upon the Miles and Huberman (1994) framework to analyze qualitative data. Data analysis suggested that informal learning among frontline employees would lead to four strategies: (i) to be polite and respect patrons; (ii) to uncover patrons’ emotional status from their body language; (iii) to manage patrons’ emotions in their gaming pursuit; and (iv) to self-regulate emotions to the demands of a service encounter

'Ephemerality’ in game development: opportunitiees and challenges

Ephemeral Computation (Eph-C) is a newly created computation paradigm, the purpose of which is to take advantage of the ephemeral nature (limited lifetime) of computational resources. First we speak of this new paradigm in general terms, then more specifically in terms of videogame development. We present possible applications and benefits for the main research fields associated with videogame development. This is a preliminary work which aims to investigate the possibilities of applying ephemeral computation to the products of the videogame industry. Therefore, as a preliminary work, it attempts to serve as the inspiration for other researchers or videogame developers.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Bottom-up radio: creating a new media format using living lab research

This study resulted in the creation of a new media format for urban youth, adopting a living lab-approach, as current studies have shown that this group is currently not reached with the contemporary media offer. Living lab research is a state-of-the art methodology that aims at involving end-users in the innovation process over a longer time span, combining both quantitative and qualitative research techniques and tools. In a first phase, a panel of urban youngsters was created using an intake survey (N=290). These data were analyzed resulting in three distinct types of urban youngsters. In a second phase, a qualitative research trajectory was organized in order to refine the three profiles and get an insight in their media use, digital skills, media preferences and needs with regards to the current media offer. Research methods during this phase included diary studies, participatory observation during workshops and probe research. In a third phase, co-creation sessions were organized with youngsters from the urban panel in order to get feedback on a concept that was iteratively developed during the first two phases of the project. Results show that mobile devices and social media are important for these urban youngsters and that most of these youngsters have quite some creative skills. Radio seems to be a less popular medium, although they spend a significant amount of time listening to music. Further, results show that these youngsters are in need of a platform which stimulates community building and offers a space to express their creativity. A third requirement for the development of a new media format that would meet the needs of these youngers is a format that provides space for local elements and niche markets. This all resulted in the launch of Chase, an urban, crowdsourced radio station

Individual Differences in Cyber Security

A survey of IT professionals suggested that despite technological advancement and organizational procedures to prevent cyber-attacks, users are still the weakest link in cyber security (Crossler, 2013). This suggests it is important to discover what individual differences may cause a user to be more or less vulnerable to cyber security threats. Cyber security knowledge has been shown to lead to increased learning and proactive cyber security behavior (CSB). Self-efficacy has been shown to be a strong predictor of a user’s intended behavior. Traits such as neuroticism have been shown to negatively influence cyber security knowledge and self-efficacy, which may hinder CSB. In discovering what individual traits may predict CSB, users and designers may be able to implement solutions to improve CSB. In this study, 183 undergraduate students at San José State University completed an online survey. Students completed surveys of self-efficacy in information security, and cyber security behavioral intention, as well as a personality inventory and a semantic cyber security knowledge quiz. Correlational analyses were conducted to test hypotheses related to individual traits expected to predict CSB. Results included a negative relationship between neuroticism and self-efficacy and a positive relationship between self-efficacy and CSB. Overall, the results support the conclusion that individual differences can predict self-efficacy and intention to engage in CSB. Future research is needed to investigate whether CSB is influenced by traits such as neuroticism, if CSB can be improved through video games, and which are the causal directions of these effects

Speech-based recognition of self-reported and observed emotion in a dimensional space

The differences between self-reported and observed emotion have only marginally been investigated in the context of speech-based automatic emotion recognition. We address this issue by comparing self-reported emotion ratings to observed emotion ratings and look at how differences between these two types of ratings affect the development and performance of automatic emotion recognizers developed with these ratings. A dimensional approach to emotion modeling is adopted: the ratings are based on continuous arousal and valence scales. We describe the TNO-Gaming Corpus that contains spontaneous vocal and facial expressions elicited via a multiplayer videogame and that includes emotion annotations obtained via self-report and observation by outside observers. Comparisons show that there are discrepancies between self-reported and observed emotion ratings which are also reflected in the performance of the emotion recognizers developed. Using Support Vector Regression in combination with acoustic and textual features, recognizers of arousal and valence are developed that can predict points in a 2-dimensional arousal-valence space. The results of these recognizers show that the self-reported emotion is much harder to recognize than the observed emotion, and that averaging ratings from multiple observers improves performance

Student attitudes to games-based skills development: learning from video games in higher education

Qualitative interview data is presented in support of previously-published quantitative evidence that suggests commercial video games may be used to develop useful skills and competencies in undergraduate students. The purpose of the work described here was to document the attitudes of those students involved in the quantitative study and to explore how the game-based intervention was perceived. To this end, student attitudes to the use of specified games to develop communication skill, resourcefulness and adaptability are examined. A broadly positive perception of the games' efficacy for skills development is revealed, and the aspects of game play that students believe contribute to skills development are discussed. These aspects include the need to communicate with team mates in order to succeed, and the fluid, unpredictable nature of in-game challenges. It is suggested that while the games played an important role in skills development, interaction between students, facilitated by game play, was also a significant factor