Killer applications, such as Excel and other ones, may be retrospectively considered as potential excellent Learning Environments in different specific domains and also in meta-cognitive skills even if there was no learning intention neither in the designer nor in the user. We present here a patented methodology for knowledge acquisition and construction widely and successfully used for five ye...

The Center of training for regional integration (CEFIR, in Spanish) was founded more than 20 years with the firm intention to dedicate efforts on issues of regional integration in the four countries of MERCOSUR. Since 2008 has promoted the creation of a platform for elearning and delivered some courses in blended learning and e-learning mode, for training in regional integration issues. E-learn...

Recent model-free reinforcement learning algorithms have proposed incorporating learned dynamics models as a source of additional data with the intention of reducing sample complexity. Such methods hold the promise of incorporating imagined data coupled with a notion of model uncertainty to accelerate the learning of continuous control tasks. Unfortunately, they rely on heuristics that limit us...

The emerging automated driving technology poses a new challenge to driver-automation collaboration, which requires mutual understanding between humans and machines through their intention identifications. In this article, oriented by human–machine understanding, driver steering prediction method is proposed better understand human driver's expectation during driver–vehicle interaction. predicte...

We investigate the complexity of learning from restricted sets of training examples. With the intention to make learning easier we introduce two types of restrictions that describe the permitted training examples. The strength of the restrictions can be tuned by choosing speciic parameters. We ask how strictly their values must be limited to turn NP-complete learning problems into polynomial-ti...

In this article, we modeled image target tracking into reinforcement learning framework, and we proposed a two-step reinforcement learning algorithm for target tracking. In this algorithm, we set multiple tracker agent to track the pixel of target, the intention of reinforcement learning is to achieve tracking strategy of every tracker agent, we divided each learning step of tracker into two pa...

This paper briefly introduces Topolor, a social personalized adaptive e-learning system, which aims at improving fine-grained social interaction in the learning process in addition to applying classical adaptation based on user modeling. Here, we present the main features of Topolor and its preliminary evaluation that showed high system usability from a student’s perspective. The intention is t...

Computer corpora have many potential applications in teaching and learning languages, the most direct of which – when the learners explore a corpus themselves – has become known as data-driven learning (DDL). Despite considerable enthusiasm in the research community and interest in higher education, the approach has not made major inroads to mainstream language teaching. This paper explores som...