In many multiagent approaches, it is usual to assume the existence of a common ontology among agents. However, in dynamic systems, the existence of such an ontology is unrealistic ...
Abstract. Inverse reinforcement learning addresses the general problem of recovering a reward function from samples of a policy provided by an expert/demonstrator. In this paper, w...
Creation of the reusable learning content in the process of work is a challenging but promising trend in e-learning and knowledge management. While the main research focus nowadays...
For many supervised learning tasks it is very costly to produce training data with class labels. Active learning acquires data incrementally, at each stage using the model learned...
In this paper, we propose a framework for the design of learning activities, which follows the key idea of the “Learning-for-Use” model and adopts characteristics from the exp...
Agoritsa Gogoulou, Evangelia Gouli, Maria Grigoria...