this case study investigates the effects of robot assisted language learning (rall) on english vocabulary learning and retention of iranian children with high-functioning autism. two groups of three male students (6-10 years old) with high-functioning autism participated in the current study. the humanoid robot nao was used as a teacher assistant to teach english to the rall group. both rall an...

A kind of brand-new robot, quantum robot, is proposed through fusing quantum theory with robot technology. Quantum robot is essentially a complex quantum system and it is generally composed of three fundamental parts: MQCU (multi quantum computing units), quantum controller/actuator, and information acquisition units. Corresponding to the system structure, several learning control algorithms in...

In this paper, we present flexMLfD, a robot independent and task independent demonstration learning system that supports a variable number of robot learners. Our approach is based on the Confidence-Based Autonomy (CBA) demonstration learning algorithm, which provides the means for a single robot to learn a task policy through interaction with a human teacher. The generalized representation and ...

This paper argues how robot learning can be accelerated by a developmental approach that changes the capability of the learning robot (robot development) and/or the complexity of the environment (environmental development). “Robot development” means that the perceptual, cognitive, and behavioral capabilities of the learning robot change from immature to mature states in accordance with learning...

We present a case study of reinforcement learning on a real robot, and we show how the need to perform a large number of experimental learning runs on a real robot and in a systematic way has required to redesign some of the robot hardware. We describe in detail the design of the robot and present results of the learning algorithm.

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of soci...

This paper presents a hybrid method for learning a dynamic strategy for a robot soccer team. In this method, an imitation learning scheme based on observed robot soccer games is used as a seed for an experience-guided learning scheme based on reinforcement learning. A lack in the application of classic reinforcement learning to the robot soccer problem is the high number of states to be analyze...

For path planning of mobile robot, the traditional Q learning algorithm easy to fall into local optimum, slow convergence etc. issues, this paper proposes a new greedy strategy, multi-target searching of Q learning algorithm. Don't need to create the environment model, the mobile robot from a single-target searching transform into multitarget searching an unknown environment, firstly, by the dy...

Despite many promising results from the use of reinforcement learning in simulated robot worlds, its use in real robot worlds is relatively rare. This paper addresses challenges related to real robot worlds and shows how reinforcement learning combined with linear function approximation can solve many of them. Experiments are performed using a light-seeking robot built with the Lego Mindstorms ...

Robot learning consists of a multitude of machine learning approaches, particularly reinforcement learning, inverse reinforcement learning, and regression methods, that have been adapted su ciently to domain so that they allow learning in complex robot systems such as helicopters, apping-wing ight, legged robots, anthropomorphic arms and humanoid robots. While classical arti cial intelligence-b...