In this paper we investigate using multiple mappings for transfer learning in reinforcement learning tasks. We propose two different transfer learning algorithms that are able to manipulate multiple inter-task mappings for both model-learning and model-free reinforcement learning algorithms. Both algorithms incorporate mechanisms to select the appropriate mappings, helping to avoid the phenomen...

54 AI MAGAZINE Observations of human reasoning motivate AI research on transfer learning (TL) and case-based reasoning (CBR). Our ability to transfer knowledge and expertise from understood domains to novel ones has been thoroughly documented in psychology and education (for example, Thorndike and Woodworth 1901; Perkins and Salomon 1994; Bransford, Brown, and Cocking 2000), among other discipl...

Quantum machine learning (QML) has aroused great interest because it the potential to speed up established classical processes. However, present QML models can merely be trained on dataset of single domain interest. This severely limits application scenario where only small datasets are available. In this work, we have proposed a model that allows transfer knowledge from one encoded by quantum ...

Semi-supervised and cross-lingual knowledge transfer learnings are two strategies for boosting performance of lowresource speech recognition systems. In this paper, we propose a unified knowledge transfer learning method to deal with these two learning tasks. Such a knowledge transfer learning is realized by fine-tuning of Deep Neural Network (DNN). We demonstrate its effectiveness in both mono...

Transfer learning aims at reusing the knowledge in some source tasks to improve the learning of a target task. Many transfer learning methods assume that the source tasks and the target task be related, even though many tasks are not related in reality. However, when two tasks are unrelated, the knowledge extracted from a source task may not help, and even hurt, the performance of a target task...

Transfer of learning occurs when learning in one context enhances (positive transfer) or undermines (negative transfer) a related performance in another context. Transfer includes near transfer (to closely related contexts and performances) and far transfer (to rather different contexts and performances). Transfer is crucial to education, which generally aspires to impact on contexts quite diff...