The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more e...
We experimented on task-level robot learning based on bi-directional theory. The via-point representation was used for ‘learning by watching’. In our previous work, we had a r...
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...
The selection and control of action is a critical problem for both biological and machine animated systems that must operate in complex real world situations. Visually guided eye ...
A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the pr...