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» Learning Qualitative Models of Dynamic Systems
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AI
1999
Springer
13 years 8 months ago
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning a
In this paper, we first discuss the meaning of physical embodiment and the complexity of the environment in the context of multi-agent learning. We then propose a vision-based rei...
Minoru Asada, Eiji Uchibe, Koh Hosoda
CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 4 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
NN
2010
Springer
225views Neural Networks» more  NN 2010»
13 years 7 months ago
Learning to imitate stochastic time series in a compositional way by chaos
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Jun Namikawa, Jun Tani
ESANN
1998
13 years 9 months ago
Lazy learning for control design
This paper presents two local methods for the control of discrete-time unknown nonlinear dynamical systems, when only a limited amount of input-output data is available. The modeli...
Gianluca Bontempi, Mauro Birattari, Hugues Bersini
ISBI
2008
IEEE
14 years 9 months ago
Segmentation of the evolving left ventricle by learning the dynamics
We propose a method for recursive segmentation of the left ventricle (LV) across a temporal sequence of magnetic resonance (MR) images. The approach involves a technique for learn...
Walter Sun, Müjdat Çetin, Raymond Chan...