In this paper, we deal with imitation learning of arm movements in humanoid robots. Hidden Markov Models (HMM) are used to generalize movements demonstrated to a robot multiple tim...
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
We describe an application of inductive logic programming to transfer learning. Transfer learning is the use of knowledge learned in a source task to improve learning in a related ...
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richa...
As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...