1 - This paper discusses an architecture designed to provide support for the development of state transition models for an object-oriented distributed environment. The state transi...
Bernard T. Barcio, Srini Ramaswamy, K. Suzanne Bar...
This paper presents a method of vision-based reinforcement learning by which a robot learns to shoot a ball into a goal, and discusses several issues in applying the reinforcement...
Programmable parts orienting is an important capability for exible automation systems. Here we study how a part grasped in an unknown orientation by a force-controlled robot can b...
2 Multi-view Integration: A Review We address the problem of constructing a boundary model of an object when the input consists of a set of points that lie on its surface. We assum...
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...