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Cell Cycle Learn (CCL) is a learning game designed for undergraduate students in Biology to learn common knowledge about the cell-division cycle along with practical skills related with setting up an experiment and the scientific method in general. In CCL, learners are guided through the process of formulating hypotheses, conducting virtual experiments and analysing the results in order to validate...
In this paper I review gaze-based interaction, distinguishing eye movement analysis from synthesis in virtual reality and games for serious applications. My focus is on four forms of gaze-based interaction: diagnostic, active, passive, and expressive. In discussing each, I briefly review seminal results and recent advancements, highlighting outstanding research problems.
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.
Exertion games form a vastly expanding field, crossing over to machine learning and user studies, with studies of qualitative traits of actions, such as the player's level of expertise. In this work, we show how simple shape descriptors based on variance features fare on such a demanding task. We formulate two variance-based features and experiment on a demanding sports related dataset, captured with...
The aim of this paper is to compare two different types of filter for the diving video processing. The two filters are a boolean filter and a fuzzy filter. These filters are applied for improving the diving video analysis aimed to introduce quantitative tools and diving performance measurement and therefore to improve training. The aim of the filter is to identify the athlete in the video to further...
The relevance of the article is determined by a new socio-cultural situation, conditioned by the development of the information society. There are unknown cultural practices, intellectual and emotional needs, value orientations against the background of a significant decrease in the communicative and cognitive abilities of students, necessary for functioning not only in the educational environment...
Understanding human behavior is crucial in anticipating adversarial actions during cyberattacks. The Criminal Justice (CJ) discipline offers the necessary frameworks to unpack the complex facets of adversarial behavior and movement, and should therefore be leveraged for their possible contributions to the area of proactive cybersecurity. Yet the discipline remains weak at training current and future...
Neurofeedback training is one type of the biofeedback training that allows the subject do self-regulation during the training according to his/her real-time brain activities recognized from Electroencephalogram (EEG) and given to him/her through visual, audio or haptic feedback. The Neurofeedback training has been proved to be helpful in improvement of cognitive abilities not only for patients with...
This paper presents recent additions to our Wheelchair-VR application, in particular the use of different drive configurations. We have previously shown that Wheelchair-VR can be used to improve driving skills. Here we consider the utility of the application in allowing users who are in the process of purchasing or upgrading a wheelchair to experience different configurations and options in a cost-effective...
The use of statistical and machine learning approaches, such as Markov chains, for procedural content generation (PCG) has been growing in recent years in the field of Game AI. However, many of these level generation approaches account for only the structural properties of the levels. We developed multi-layered representations of levels, where each layer is designed to capture distinct gameplay information...
In view of the problems of the current teaching content being out of touch with social needs and students' poor practical abilities and other issues, this paper analyzes the new international software engineering training model. Based on the iterative optimization method of updating the teaching idea, optimizing the curriculum system, strengthening the schoolenterprise cooperation and improving teachers'...
This paper investigates the potential of combining deep learning and neuroevolution to create a bot for a simple first person shooter (FPS) game capable of aiming and shooting based on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition and translating raw pixels to compact feature representations, while the evolving network takes those features as inputs...
Artificial intelligence is a new subject which has been applied in many fields. In recent years, many countries have been promoting quality education, and promotion of the culture of all the students and the overall quality of research and solve problems of practical ability, and multifaceted Intelligent students also advocated the development of a variety of intelligence, and that the goal of quality...
We present ongoing work on a tool that consists of two parts: (i) A raw micro-level abstract world simulator with an interface to (ii) a 3D game engine, translator of raw abstract simulator data to photorealistic graphics. Part (i) implements a dedicated cellular automata (CA) on reconfigurable hardware (FPGA) and part (ii) interfaces with a deep learning framework for training neural networks. The...
In game artificial intelligence (AI), two common directions for developing non-human computer players are strong AI and human-like AI. Human-like AI aims at making computer agents behave like humans. In this direction, NeuroEvolution (NE), which is a combination of an artificial neural network (ANN) and an evolutionary algorithm (EA), had been frequently used to a make computer agent to behave like...
In recent years, image generation using Convolutional Neural Networks (CNNs) has become increasingly popular in the computer vision domain. However, there is less attention on using CNNs for sprite generation for games. A possible reason for this is that the amount of available sprite data in games is significantly less than in other domains, which typically use hundreds of thousands of images, or...
Neuroevolution has proven effective at many re-inforcement learning tasks, including tasks with incomplete information and delayed rewards, but does not seem to scale well to high-dimensional controller representations, which are needed for tasks where the input is raw pixel data. We propose a novel method where we train an autoencoder to create a comparatively low-dimensional representation of the...
In a game it is often the case that there are multiple roles or types of actors with different goals. One possible target for automatic content generation is to create multiple different software agents for these distinct roles. This paper outlines a technique, based on the multiple worlds model, for creating such actors via evolution. The objective function is based on the performance of the actors...
Attention Deficit Hyperactivity Disorder (ADHD) is a disorder of performance with core symptoms of inattention, hyperactivity or impulsivity. In adults, hyperactivity may decrease, but struggles with inattention or impulsivity may continue. Neurofeedback game can be used as an alternative approach to enhance attention. In this pilot study, we developed a neurofeedback game for attention training in...
Deep learning for human action recognition in videos is making significant progress, but is slowed down by its dependency on expensive manual labeling of large video collections. In this work, we investigate the generation of synthetic training data for action recognition, as it has recently shown promising results for a variety of other computer vision tasks. We propose an interpretable parametric...
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