24 search results - page 2 / 5 » Factored MCTS for Large Scale Stochastic Planning |
IJCAI
2007
13 years 6 months ago
2007
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
JMLR
2010
13 years 3 months ago
2010
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...
ICCAD
2005
IEEE
13 years 10 months ago
2005
IEEE
— Balanced truncation (BT) model order reduction (MOR) is known for its superior accuracy and computable error bounds. Balanced stochastic truncation (BST) is a particular BT pro...
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
MOBICOM
2006
ACM
13 years 11 months ago
2006
ACM
Mobile sensors cover more area over a period of time than the same number of stationary sensors. However, the quality of coverage achieved by mobile sensors depends on the velocit...