Boltzmann machines are often used as building blocks in greedy learning of deep networks. However, training even a simplified model, known as restricted Boltzmann machine (RBM), can be extremely laborious: Traditional learning algorithms often converge only with the right choice of the learning rate scheduling and the scale of the initial weights. They are also sensitive to specific data repres...

This article presents two longitudinal studies that investigated expertise reversal effects in journal writing. In Experiment 1, students wrote regular journal entries over a whole term. The experimental group received a combination of cognitive and metacognitive prompts. The control group received no prompts. In the first half of the term, the experimental group applied more cognitive and meta...

Incentive learning is the process via which animals update changes in the value of rewards. Current evidence suggests that, for food rewards in rats, this learning process involves the amygdala. However, it remains unclear whether this learning undergoes protein synthesis-dependent consolidation and “reconsolidation” processes in the lateral and basal nuclei of amygdala. Accordingly, we examine...

Restricted Boltzmann machines (RBMs) are often used as building blocks in greedy learning of deep networks. However, training this simple model can be laborious. Traditional learning algorithms often converge only with the right choice of metaparameters that specify, for example, learning rate scheduling and the scale of the initial weights. They are also sensitive to specific data representati...

According to cognitive load theorists, the incorporation of extraneous features, such as pedagogical agents, into the learning environment can introduce extraneous cognitive load and thus interfere with learning outcome scores. In this study, the influence of a pedagogical agent’s presence in an instructional video was compared to a video that did not contain a pedagogical agent. The results in...

Incentive learning is the process via which animals update changes in the value of rewards. Current evidence suggests that, for food rewards in rats, this learning process involves the amygdala. However, it remains unclear whether this learning undergoes protein synthesis-dependent consolidation and "reconsolidation" processes in the lateral and basal nuclei of amygdala. Accordingly, we examine...

In conditional visuomotor learning, several arbitrary associations between visual cues and motor responses have to be learned by trial and error at the same time. Monkeys, as humans, do not achieve this task by randomly trying each possible association. Rather, they use a strategy that organizes sequentially the acquisition of individual stimulus-response associations. Accordingly, neuronal rec...

Use of adaptive energy management strategies is essential in improving energy utilization, efficiency, and sustainable operation of embedded systems. Accordingly, this paper presents embedded system applications, which are suitable for employing adaptive energy management utilized reinforcement learning. We proposed rewarding function for embedded system applications in stimulating the learning...

The successful management of learning and knowledge has become a critical success factor for organisations in today’s knowledge-intensive business world. Reflection on work practice has been identified as one of the central mechanisms of learning at work. It leads to a better understanding of work-related experiences and can guide future behavior. However, it has not been discussed so far how r...