Open PhD Workshop on Technology-Enhanced Learning and Semantics, Software and Services

The 7FP project SISTER focuses, especially, on strengthening the PhD and PostDoc level of education and training of researchers, and thus attracting more young scientists to the research profession and retaining them. The project SISTER is structured around two ICT strategic research areas - Software and services, and Intelligent Content and Semantics. The research workshops and seminars will support the research in the particular area through brainstorming sessions, discussions and strategic planning. Some of them will be of benefit to the PhD students and Post Docs and the advancement in their careers, while others will be devoted to further research collaboration in selected EU research programmes. The main research areas addressed are: Creation of digital libraries with intelligent content. Semantic annotation of digital content - Creation of ontologies for the digital content in the libraries. Semantic annotation of the learning materials in the repositories. The created ontologies and their semantic annotation will allow searching materials using semantic web techniques. Development of adaptive intelligent learning systems based on intelligent ontologies and digital learning materials. New innovative pedagogical approaches, assessment models and organisational models for lifelong competence development. Software for the effective support of users who create, store, use and exchange knowledge resources, learning activities, units of learning and competence development programmes within a learning network. Models and tools for competence development into a common, easy to use infrastructure. Training programs to learn users how to work with the infrastructure, and to train instructors and companies (specifically SMEs) to deliver services using the infrastructure. Responsive environments for technology-enhanced learning higher education and business organisations "that motivate, engage and inspire learners, and which can be embedded in the business processes and human resources management systems of organisations". Special attention will be given to using the research outcomes related to Intelligent Content and Semantics and Digital Libraries for building intelligent Adaptive and intuitive learning systems and Web 2.0 oriented applications. Development of a semantics-based reference frameworks for the conceptualisation of learning content, learning objectives, and teaching strategies, and the implementation of pedagogically-driven and semantically-enhanced adaptive learning systems. This will lead to consolidating existing theoretical and technological frameworks for explicitly modelling educational content, teaching strategies, and learner characteristics, and integrating them under a common semantic model.Open PhD Workshop on Technology-Enhanced Learning and Semantics, Software and Services in conjunction with the 13th International Conference on Artificial Intelligence: Methodology, Systems, Applications - AI@Work (AIMSA 2008) 04-06 September, Varna, Bulgari

Intelligent Escape of Robotic Systems: A Survey of Methodologies, Applications, and Challenges

Intelligent escape is an interdisciplinary field that employs artificial intelligence (AI) techniques to enable robots with the capacity to intelligently react to potential dangers in dynamic, intricate, and unpredictable scenarios. As the emphasis on safety becomes increasingly paramount and advancements in robotic technologies continue to advance, a wide range of intelligent escape methodologies has been developed in recent years. This paper presents a comprehensive survey of state-of-the-art research work on intelligent escape of robotic systems. Four main methods of intelligent escape are reviewed, including planning-based methodologies, partitioning-based methodologies, learning-based methodologies, and bio-inspired methodologies. The strengths and limitations of existing methods are summarized. In addition, potential applications of intelligent escape are discussed in various domains, such as search and rescue, evacuation, military security, and healthcare. In an effort to develop new approaches to intelligent escape, this survey identifies current research challenges and provides insights into future research trends in intelligent escape.Comment: This paper is accepted by Journal of Intelligent and Robotic System