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AROBOTS
2004
99views more  AROBOTS 2004»
13 years 7 months ago
Bayesian Robot Programming
We propose a new method to program robots based on Bayesian inference and learning. It is called BRP for Bayesian Robot Programming. The capacities of this programming method are d...
Olivier Lebeltel, Pierre Bessière, Julien D...
JMLR
2010
148views more  JMLR 2010»
13 years 2 months ago
A Generalized Path Integral Control Approach to Reinforcement Learning
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
HYBRID
2005
Springer
14 years 1 months ago
Learning Multi-modal Control Programs
Abstract. Multi-modal control is a commonly used design tool for breaking up complex control tasks into sequences of simpler tasks. In this paper, we show that by viewing the contr...
Tejas R. Mehta, Magnus Egerstedt
IJCAI
1997
13 years 8 months ago
Combining Knowledge Acquisition and Machine Learning to Control Dynamic Systems
This paper presents an interactive method for building a controller for dynamic systems by using a combination of knowledge acquisition and machine learning techniques. The aim is...
G. M. Shiraz, Claude Sammut
ICRA
2010
IEEE
131views Robotics» more  ICRA 2010»
13 years 6 months ago
Graphical state-space programmability as a natural interface for robotic control
— We present an interface for controlling mobile robots that combines aspects of graphical trajectory specification and state-based programming. This work is motivated by common...
Junaed Sattar, Anqi Xu, Gregory Dudek, Gabriel Cha...