A theoretical framework for grounding language is introduced that provides a computational path from sensing and motor action to words and speech acts. The approach combines conce...
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
We propose dynamical systems trees (DSTs) as a flexible model for describing multiple processes that interact via a hierarchy of aggregating processes. DSTs extend nonlinear dynam...
— An autonomous robot system that is to act in a real-world environment is faced with the problem of having to deal with a high degree of both complexity as well as uncertainty. ...
Machine Learning algorithms can act as a valuable analytical tool in design research. In this paper, we demonstrate the application of a decision tree learning algorithm for desig...