69 search results - page 13 / 14 » Random Sampling of States in Dynamic Programming |
UAI
2004
13 years 7 months ago
2004
We show that the class of strongly connected graphical models with treewidth at most k can be properly efficiently PAC-learnt with respect to the Kullback-Leibler Divergence. Prev...
ICST
2010
IEEE
13 years 4 months ago
2010
IEEE
—Mutation testing measures the adequacy of a test suite by seeding artificial defects (mutations) into a program. If a test suite fails to detect a mutation, it may also fail to...
VALUETOOLS
2006
ACM
13 years 11 months ago
2006
ACM
Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the or...
GECCO
2007
Springer
13 years 12 months ago
2007
Springer
A new family of "Distribution Replacement” operators for use in steady state genetic algorithms is presented. Distribution replacement enforces the members of the populatio...
ATAL
2005
Springer
13 years 11 months ago
2005
Springer
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...