Recently it has been shown that deep neural networks can learn to play Atari games by directly observing raw pixels of the playing area. We show how apprenticeship learning can be applied in this setting so that an agent can learn to perform a task (i.e. play a game) by observing the expert, without any explicitly provided knowledge of the game’s internal state or objectives. Background Mnih et...

A training platform online is an environment that affords the conduct of long distance teaching. It’s an online training environment that is made of tools to facilitate the use of the system various functional devices. It also allows to simplify long distance consultation of teaching contents, the tailoring of the apprenceship and the service protector. It as well allows to implement flexible s...

LEAP is a coached practice environment that optimizes the learning process by maintaining and consulting a detailed student model. LEAP calculates a student model score for every action, exercise, and topic the student tries, then uses the scores both to provide feedback to the student and to select topics, exercises and actions for the student to practice. Using the student model to focus prac...

Embodied Conversational Agents (ECAs) are emerging as a key component to allow human interact with machines. Applications are numerous and ECAs can reduce the aversion to interact with a machine by providing user-friendly interfaces. Yet, ECAs are still unable to produce social signals appropriately during their interaction with humans, which tends to make the interaction less instinctive. Espe...

Inverse reinforcement learning (IRL) addresses the problem of recovering a task description given a demonstration of the optimal policy used to solve such a task. The optimal policy is usually provided by an expert or teacher, making IRL specially suitable for the problem of apprenticeship learning. The task description is encoded in the form of a reward function of a Markov decision process (M...

This paper presents a methodology, called CAPTAIN, to build adaptive agents in an integrated framework that facilitates both building agents through knowledge elicitation and interactive apprenticeship learning from subject matter experts, and making these agents adapt and improve during their normal use through autonomous learning. Such an automated adaptive agent consists of an adversarial pl...

Apprenticeship systems are essentially based on the voluntary participation of firms that provide, and usually also finance, training positions, often incurring considerable net costs. One potential, yet under-researched explanation for this behavior is act in accordance with norms expectations they face local labor market which operate. In paper, we focus Swiss apprenticeship system ask whethe...

Three situations are described where a junior doctor is required by his consultant to do something that he thinks is not in the patient's best interests. The dilemma is explored from the perspective of patients' interests being the doctor's first concern; of the importance of respect for medical teachers, and of the implications of an apprenticeship model of postgraduate medical training.

This assignment considers the use of the apprenticeship model of teaching in academic subject areas. This has been investigated by various authors since 1989. I will consider the various flavours of the techniques presented and some of the practical implications of these. I will draw from our experience running several courses where students undertake business like projects within a protective ...

This article discusses the concept of legal construction notary candidate apprenticeship within framework rechtsidee (law ideals). demonstrates that so called rechtidee has always focused on three ideals, namely certainty, justice, and benefit. With regards to apprenticeship, it is argued, however, these ideals are not sufficient. Most studies have forgotten another basic ideal, education princ...