103 search results - page 5 / 21 » Adaptive Stochastic Resource Control: A Machine Learning App... |
AMS
2007
Springer
14 years 1 months ago
2007
Springer
Autonomous robots that can adapt to novel situations has been a long standing vision of robotics, artificial intelligence, and cognitive sciences. Early approaches to this goal du...
AUSAI
2005
Springer
14 years 1 months ago
2005
Springer
This paper addresses the problem of scheduling jobs in soft real-time systems, where the utility of completing each job decreases over time. We present a utility-based framework fo...
ECML
2006
Springer
13 years 11 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
NIPS
1998
13 years 9 months ago
1998
The kernel-parameter is one of the few tunable parameters in Support Vector machines, controlling the complexity of the resulting hypothesis. Its choice amounts to model selection...