243 search results - page 11 / 49 » Learning Abstraction Hierarchies for Problem Solving |
KR
2004
Springer
14 years 2 months ago
2004
Springer
Modeling complex compositional objects in the field of the life sciences requires to solve intricate ontological problems, especially those related to parts of a whole, space and...
ICML
2003
IEEE
14 years 9 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
ICRA
2008
IEEE
14 years 3 months ago
2008
IEEE
Abstract— Learning inverse kinematics has long been fascinating the robot learning community. While humans acquire this transformation to complicated tool spaces with ease, it is...
GECCO
2010
Springer
14 years 1 months ago
2010
Springer
HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
MLG
2007
Springer
14 years 2 months ago
2007
Springer
Abstract. There are many connections between graph mining and inductive logic programming (ILP), or more generally relational learning. Up till now these connections have mostly be...