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In this paper we report on our study of the performance of Deep Reinforcement Learning (DRL) agents in performing tasks that are illustrative for human Sensor Operators (SOs) in Remotely Piloted Aircraft Systems (RPASs). Our hypothesis is that the descriptive and predictive qualities of the agent's learning process potentially allow us to identify human task requirements, training needs, selection...
This paper presents a serious game designed for children suffering from profound intellectual and multiple disabilities (PIMD) also know as multihandicap, for their evaluation and cognitive training. The specificities of these children must be taken into account for the choice of both the game feedbacks and interfaces.
Objective: The purpose of this study was to determine the effect of Jenga game brain training for cognitive performance and EEG activity in Thai healthy older adults. Material and Methods: Six participants were participated. Participants were instructed to practice Jenga gam brain training. During practice memory and attention games, EEG activity were recorded by using the lightweight EEG device,...
Serious games have a great potential for training and educating people in novel and engaging ways. However, little empirical research has been done on the effectiveness of serious games and, although early findings do point in a moderately positive direction, even less is known about why some games succeed in effectively educating while others donpsilat. We therefore propose a serious game, Code Red:...
This paper presents the results of an experimental study on designing for self-efficacy in a game based driving simulator. Self-efficacy refers to how peoplepsilas beliefs in their capabilities affect their actions. The results show that the design of the feedback system can be used to increase self-efficacy measures thus affecting performance in a driving simulator environment. Self-efficacy has...
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