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» Learning to Control in Operational Space
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IROS
2008
IEEE
125views Robotics» more  IROS 2008»
15 years 10 months ago
Dynamic correlation matrix based multi-Q learning for a multi-robot system
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
Hongliang Guo, Yan Meng
143
Voted
NIPS
1993
15 years 5 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
ISCI
2008
83views more  ISCI 2008»
15 years 4 months ago
A diversity maintaining population-based incremental learning algorithm
In this paper we propose a new probability update rule and sampling procedure for population-based incremental learning. These proposed methods are based on the concept of opposit...
Mario Ventresca, Hamid R. Tizhoosh
JMLR
2002
133views more  JMLR 2002»
15 years 3 months ago
Learning Precise Timing with LSTM Recurrent Networks
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Felix A. Gers, Nicol N. Schraudolph, Jürgen S...
ISVC
2010
Springer
15 years 2 months ago
Automatic Learning of Gesture Recognition Model Using SOM and SVM
In this paper, we propose an automatic learning method for gesture recognition. We combine two different pattern recognition techniques: the SelfOrganizing Map (SOM) and Support Ve...
Masaki Oshita, Takefumi Matsunaga