Using learning algorithm behavior to chart task space: The DICES distance

Using learning algorithm behavior to chart task space: The DICES distance

In theory, learning is not possible over all tasks in general. In practice, the tasks for which learning is desired exhibit significant regularity, which makes learning practical. For the most effective learning, it is valuable to understand the nature of this regularity and how it manifests in the tasks where learning is applied. This research presents the DICES distance metric for finding sim...

the relationship between using language learning strategies, learners’ optimism, educational status, duration of learning and demotivation

with the growth of more humanistic approaches towards teaching foreign languages, more emphasis has been put on learners’ feelings, emotions and individual differences. one of the issues in teaching and learning english as a foreign language is demotivation. the purpose of this study was to investigate the relationship between the components of language learning strategies, optimism, duration o...

Task Space Behavior Learning for Humanoid Robots using Gaussian Mixture Models

In this paper a system was developed for robot behavior acquisition using kinesthetic demonstrations. It enables a humanoid robot to imitate constrained reaching gestures directed towards a target using a learning algorithm based on Gaussian Mixture Models. The imitation trajectory can be reshaped in order to satisfy the constraints of the task and it can adapt to changes in the initial conditi...

Learning English Grapheme Segmentation Using the Iterated Version Space Algorithm

Our unique approach for learning English grapheme segmen tation LE GS rules using the Iterated Version Space Algorithm IVSA is presented After de ning the problem and our representation for the instances and hypotheses we illustrate the LE GS approach by trac ing a speci c example Experimental results based on a ten fold testing methodology are given to show the performance of the LE GS learnin...

Adaptive State-Space Quantisation and Multi-Task Reinforcement Learning Using . . .