Imperial College London

Professor Yiannis Demiris

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Human-Centred Robotics, Head of ISN



+44 (0)20 7594 6300y.demiris Website




1014Electrical EngineeringSouth Kensington Campus






BibTex format

author = {Lee, K and Demiris, Y},
doi = {10.1109/DEVLRN.2011.6037332},
pages = {1--6},
publisher = {IEEE},
title = {Towards incremental learning of task-dependent action sequences using probabilistic parsing},
url = {},
year = {2011}

RIS format (EndNote, RefMan)

AB - We study an incremental process of learning where a set of generic basic actions are used to learn higher-level task-dependent action sequences. A task-dependent action sequence is learned by associating the goal given by a human demonstrator with the task-independent, general-purpose actions in the action repertoire. This process of contextualization is done using probabilistic parsing. We propose stochastic context-free grammars as the representational framework due to its robustness to noise, structural flexibility, and easiness on defining task-independent actions. We demonstrate our implementation on a real-world scenario using a humanoid robot and report implementation issues we had.
AU - Lee,K
AU - Demiris,Y
DO - 10.1109/DEVLRN.2011.6037332
EP - 6
PY - 2011///
SP - 1
TI - Towards incremental learning of task-dependent action sequences using probabilistic parsing
UR -
UR -
UR -
ER -