30 search results - page 2 / 6 » Symmetric approximate linear programming for factored MDPs w... |
UAI
2004
13 years 10 months ago
2004
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...
NIPS
2004
13 years 10 months ago
2004
We examine the problem of approximating, in the Frobenius-norm sense, a positive, semidefinite symmetric matrix by a rank-one matrix, with an upper bound on the cardinality of its...
ICML
2002
IEEE
14 years 9 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 ...
AIPS
2009
13 years 9 months ago
2009
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...
SODA
2012
ACM
11 years 11 months ago
2012
ACM
We give a constant factor approximation algorithm for the following generalization of the k-median problem. We are given a set of clients and facilities in a metric space. Each fa...