508 search results - page 15 / 102 » Learning for stochastic dynamic programming |
118
Voted
GECCO
2009
Springer
15 years 8 months ago
2009
Springer
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
119
click to vote
JSAI
2005
Springer
15 years 7 months ago
2005
Springer
Abstract. This paper is concerned with algorithms for the logical generalisation of probabilistic temporal models from examples. The algorithms combine logic and probabilistic mode...
102
click to vote
ICC
2007
IEEE
15 years 8 months ago
2007
IEEE
—We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multiattribute utility theory, kernel learning and stochastic gradient ...
153
click to vote
EUROGP
2006
Springer
15 years 5 months ago
2006
Springer
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation...
129
click to vote
NIPS
1993
15 years 3 months ago
1993
Stochastic optimization algorithms typically use learning rate schedules that behave asymptotically as (t) = 0=t. The ensemble dynamics (Leen and Moody, 1993) for such algorithms ...