Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to re...
— Accurate and fast control of wheel speeds in the presence of noise and nonlinearities is one of the crucial requirements for building fast mobile robots, as they are required i...
— This paper presents a new reinforcement learning algorithm for accelerating acquisition of new skills by real mobile robots, without requiring simulation. It speeds up Q-learni...
Abstract— This paper presents a learning system that uses Qlearning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a functi...
We address the problem of autonomously learning controllers for visioncapable mobile robots. We extend McCallum's (1995) Nearest-Sequence Memory algorithm to allow for genera...
Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter,...