63 search results - page 4 / 13 » Learning Symbolic Models of Stochastic Domains |
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
FASE
2008
Springer
14 years 11 months ago
2008
Springer
Abstract. Existing algorithms for regular inference (aka automata learning) allows to infer a finite state machine by observing the output that the machine produces in response to ...
105
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NIPS
2008
14 years 11 months ago
2008
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
75
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DMIN
2006
14 years 10 months ago
2006
The stochastic discrimination (SD) theory considers learning as building models of uniform coverage over data distributions. Despite successful trials of the derived SD method in s...
PKDD
2009
Springer
15 years 4 months ago
2009
Springer
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...