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» Learning Model Complexity in an Online Environment
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NIPS
1993
15 years 1 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...
LWA
2007
15 years 1 months ago
Know the Right People? Recommender Systems for Web 2.0
Web 2.0 applications like Flickr, YouTube, or Del.icio.us are increasingly popular online communities for creating, editing and sharing content. However, the rapid increase in siz...
Stefan Siersdorfer, Sergej Sizov, Paul Clough
ECAI
2004
Springer
15 years 5 months ago
Avatars That Learn How to Behave
It is possible to model avatars that learn to simulate object manipulations and other complex actions. A number of applications may benefit from this technique including safety, e...
Adam Szarowicz, Paolo Remagnino
AAAI
2008
15 years 2 months ago
Exposing Parameters of a Trained Dynamic Model for Interactive Music Creation
As machine learning (ML) systems emerge in end-user applications, learning algorithms and classifiers will need to be robust to an increasingly unpredictable operating environment...
Dan Morris, Ian Simon, Sumit Basu
IROS
2006
IEEE
121views Robotics» more  IROS 2006»
15 years 5 months ago
Planning and Acting in Uncertain Environments using Probabilistic Inference
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Deepak Verma, Rajesh P. N. Rao