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» Using Stochastic Grammars to Learn Robotic Tasks
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IJCAI
2001
13 years 10 months ago
Robot Weightlifting By Direct Policy Search
This paper describes a method for structuring a robot motor learning task. By designing a suitably parameterized policy, we show that a simple search algorithm, along with biologi...
Michael T. Rosenstein, Andrew G. Barto
ICRA
2010
IEEE
137views Robotics» more  ICRA 2010»
13 years 7 months ago
Robot reinforcement learning using EEG-based reward signals
Abstract— Reinforcement learning algorithms have been successfully applied in robotics to learn how to solve tasks based on reward signals obtained during task execution. These r...
Iñaki Iturrate, Luis Montesano, Javier Ming...
AIIA
2007
Springer
14 years 2 months ago
Reinforcement Learning in Complex Environments Through Multiple Adaptive Partitions
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
NIPS
2001
13 years 10 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning
EMNLP
2006
13 years 10 months ago
Multilingual Deep Lexical Acquisition for HPSGs via Supertagging
We propose a conditional random fieldbased method for supertagging, and apply it to the task of learning new lexical items for HPSG-based precision grammars of English and Japanes...
Phil Blunsom, Timothy Baldwin