This paper studies iterative learning control (ILC) in a multi-agent framework. A group of agents simultaneously and repeatedly perform the same task. The agents improve their perf...
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
Abstract. Learning ranking functions is crucial for solving many problems, ranging from document retrieval to building recommendation systems based on an individual user’s prefer...
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
We present a system for visual robotic docking using an omnidirectional camera coupled with the actor critic reinforcement learning algorithm. The system enables a PeopleBot robot...