Background and purpose: The objective of this study was to assess the neurological manifestations in a series of consecutive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patients, comparing their frequency with a population hospitalized in the same period for flu/respiratory symptoms, finally not related to SARS-CoV-2. Methods: Patients with flu/respiratory symptoms admitted to Fondazione Policlinico Gemelli hospital from 14 March 2020 to 20 April 2020 were retrospectively enrolled. The frequency of neurological manifestations of patients with SARS-CoV-2 infection was compared with a control group. Results: In all, 213 patients were found to be positive for SARS-CoV-2, after reverse transcriptase polymerase chain reaction on nasal or throat swabs, whilst 218 patients were found to be negative and were used as a control group. Regarding central nervous system manifestations, in SARS-CoV-2-positive patients a higher frequency of headache, hyposmia and encephalopathy always related to systemic conditions (fever or hypoxia) was observed. Furthermore, muscular involvement was more frequent in SARS-CoV-2 infection. Conclusions: Patients with COVID-19 commonly have neurological manifestations but only hyposmia and muscle involvement seem more frequent compared with other flu diseases.

This article provides a comprehensive overview of artificial intelligence (AI) for serious games. Reporting about the work of a European flagship project on serious game technologies, it presents a set of advanced game AI components that enable pedagogical affordances and that can be easily reused across a wide diversity of game engines and game platforms. Serious game AI functionalities include player modelling (realtime facial emotion recognition, automated difficulty adaptation, stealth assessment), natural language processing (sentiment analysis and essay scoring on free texts), and believable non-playing characters (emotional and socio-cultural, non-verbal bodily motion, and lip-synchronised speech), respectively. The reuse of these components enables game developers to develop high quality serious games at reduced costs and in shorter periods of time. All these components are open source software and can be freely downloaded from the newly launched portal at gamecomponents.eu. The components come with detailed installation manuals and tutorial videos. All components have been applied and validated in serious games that were tested with real end-users.

The design of serious games requires developers to tackle pedagogical challenges calling for advanced solutions that the entertainment industry might deem too risky to pursue. One such challenge is the creation of autonomous socially intelligent characters with whom players can practice different social skills. Although there are several architectures in the field of virtual agents that are designed specifically to enable more human-like interactions, they are still not widely adopted by game studios that develop serious games, in particular for learning. In this paper, we present a virtual agent toolkit that was specifically developed with the intent of making agent-based solutions more accessible and reliable to game developers. To this end, a collaborative effort was established with a game studio that has used the toolkit to develop two different serious games. Among other advantages, the toolkit facilitated the inclusion of a dynamic model of emotions that affects not just how the character looks and acts but also how the player's performance is determined.

In this work we test the hypothesis that interacting with an intelligent virtual character in Virtual Reality (VR) has a stronger impact compared to the same interaction in a traditional non-immersive platform, both in terms of presence and believability. We designed a Social Skills Training scenario of a police interview, based on interactions observed in real cases with the help of teachers and experts from that field. To test our hypothesis, we conducted experiments with two treatments: one in VR and the other displayed on a conventional computer screen. We collected qualitative and quantitative data using instruments with elements from well-established presence and situated interaction questionnaires. Results indicate that participant perception of social presence of virtual characters is higher in VR. No significant difference in believability was observed across treatments The experimental design encourages further work on measurement of effects of social presence and its impact on design of intelligent interactions in the context of Social Skills Training environments and immersive platforms. CCS CONCEPTS • Human-centered computing → Virtual reality; • Computing methodologies → Intelligent agents.

Abstract-We present and describe CiF-CK -a social agent architecture that models reasoning about persistent social interactions to improve narrative engagement and play experience for human interactors. The architecture is inspired by McCoy et al's Comme il-Faut (CiF) architecture that represented rich social interactions between agents that included emotions, social and relationship contexts, and longer term mood. The key contribution of this work is in adapting the richness of social interactions from CiF to a first-person interaction experience and a released distribution of its implementation on the Skyrim game engine. The released modification has been successful in the player community for the popular game.

More than a decade has passed since the development of FearNot!, an application designed to help children deal with bullying through role-playing with virtual characters. It was also the application that led to the creation of FAtiMA, an affective agent architecture for creating autonomous characters that can evoke empathic responses. In this paper, we describe FAtiMA Toolkit, a collection of open-source tools that is designed to help researchers, game developers and roboticists incorporate a computational model of emotion and decision-making in their work. The toolkit was developed with the goal of making FAtiMA more accessible, easier to incorporate into different projects and more flexible in its capabilities for human-agent interaction, based upon the experience gathered over the years across different virtual environments and human-robot interaction scenarios. As a result, this work makes several different contributions to the field of Agent-Based Architectures. More precisely, FAtiMA Toolkit's library based design allows developers to easily integrate it with other frameworks, its metacognitive model affords different internal reasoners and affective components and its explicit dialogue structure gives control to the author even within highly complex scenarios. To demonstrate the use of FAtiMA Toolkit, several different use cases where the toolkit was successfully applied are described and discussed.

More than a decade has passed since the development of FearNot!, an application designed to help children deal with bullying through role-playing with virtual characters. It was also the application that led to the creation of FAtiMA, an affective agent architecture for creating autonomous characters that can evoke empathic responses. In this paper, we describe FAtiMA Toolkit, a collection of open-source tools that is designed to help researchers, game developers and roboticists incorporate a computational model of emotion and decision-making in their work. The toolkit was developed with the goal of making FAtiMA more accessible, easier to incorporate into different projects and more flexible in its capabilities for human-agent interaction, based upon the experience gathered over the years across different virtual environments and human-robot interaction scenarios. As a result, this work makes several different contributions to the field of Agent-Based Architectures. More precisely, FAtiMA Toolkit’s library based design allows developers to easily integrate it with other frameworks, its meta-cognitive model affords different internal reasoners and affective components and its explicit dialogue structure gives control to the author even within highly complex scenarios. To demonstrate the use of FAtiMA Toolkit, several different use cases where the toolkit was successfully applied are described and discussed.

The Interview Simulation for Police Officers (ISPO) is a serious game developed to train police officers in communication competencies related to the interview of victims, witnesses and suspects. It was developed by Gameware Europe in collaboration with the Portuguese Police (Policia Judiciaria) within the RAGE project. The ISPO serious game was created using the modern methodologies and practices that are used in real-life police interviews. The focus of the game is on the training of communication competencies regarding gathering information from both victims and offenders. In order to evaluate the training effectiveness of the game, we conducted a study with 194 participants where general subjective learning effectiveness, using the Perceived Competence subscale of the IMI questionnaire, and domain-specific subjective learning effectiveness using the Police Interview Competency Inventory (PICI) were measured. Overall, ISPO improved the self-perceived competence of its players. Additionally, participants changed their opinion about the attitude to conduct a successful interview. Participants’ level of importance attributed to being dominant diminished and the level of importance attributed to being more benevolent and communicative during police interviews increased. Effects were stronger in inexperienced users leading us to believe that the game is an added value for use in a police officer school.