Related papers: Developing courses with HoloRena, a framework for …
Modern scene text recognition systems often depend on large end-to-end architectures that require extensive training and are prohibitively expensive for real-time scenarios. In such cases, the deployment of heavy models becomes impractical…
Performing an overview of the benchmarking initiatives oriented towards the performance evaluation of Holonic Manufacturing Systems shows that there are very few of them. However, a comparison between all the isolated emu-lation…
Most approaches to deep reinforcement learning (DRL) attempt to solve a single task at a time. As a result, most existing research benchmarks consist of individual games or suites of games that have common interfaces but little overlap in…
From computer vision and speech recognition to forecasting trajectories in autonomous vehicles, deep learning approaches are at the forefront of so many domains. Deep learning models are developed using plethora of high-level, generic…
Formation strategy is one of the most important parts of many multi-agent systems with many applications in real world problems. In this paper, a framework for learning this task in a limited domain (restricted environment) is proposed. In…
Soft and future skills are in high demand in the modern job market. These skills are required for both technical and non-technical people. It is difficult to teach these competencies in a classical academic environment. The paper presents a…
The Hellenic Open University has embarked on a large-scale effort to enhance its textbook-based material with content that demonstrably supports the basic tenets of distance learning. The challenge is to set up a framework that allows for…
Interacting with human agents in complex scenarios presents a significant challenge for robotic navigation, particularly in environments that necessitate both collision avoidance and collaborative interaction, such as indoor spaces. Unlike…
In recent years, mobile robot navigation approaches have become increasingly important due to various application areas ranging from healthcare to warehouse logistics. In particular, Deep Reinforcement Learning approaches have gained…
Within the context of a 3D interactive strategy game, the EViE platform allows participants to unlock game features using their knowledge and skills in various thematic areas such as physics, mathematics, etc. By answering questions…
In this work, we propose a computational framework in which agents equipped with communication capabilities simultaneously play a series of referential games, where agents are trained using deep reinforcement learning. We demonstrate that…
Modern software development requires a large investment in learning application programming interfaces (APIs). Recent research found that the learning materials themselves are often inadequate: developers struggle to find answers beyond…
This paper presents an overview of Carnap, a free and open framework for the development of formal reasoning applications. Carnap's design emphasizes flexibility, extensibility, and rapid prototyping. Carnap-based applications are written…
Event scenarios are often complex and involve multiple event sequences connected through different entity participants. Exploring such complex scenarios requires an ability to branch through different sequences, something that is difficult…
Reinforcement learning (RL) has been demonstrated suitable to develop agents that play complex games with human-level performance. However, it is not understood how to effectively use RL to perform cybersecurity tasks. To develop such…
Cybersecurity incident response teams mitigate the impact of adverse cyber-related events in organisations. Field studies of IR teams suggest that at present the process of IR is under-developed with a focus on the technological dimension…
Evidence shows that software development methods, frameworks, and even practices are seldom applied in companies by following the book. Combinations of different methodologies into home-grown processes are being constantly uncovered.…
Various stakeholders with different backgrounds are involved in Smart City projects. These stakeholders define the project goals, e.g., based on participative approaches, market research or innovation management processes. To realize these…
This paper describes the development needed to support the functional and teaching requirements of iRead, a 4-year EU-funded project which produced an award-winning serious game utilising lexical and syntactical game content. The main…
Location- and context-aware services are emerging technologies in mobile and desktop environments, however, most of them are difficult to use and do not seem to be beneficial enough. Our research focuses on designing and creating a…