63 search results - page 3 / 13 » Learning Symbolic Models of Stochastic Domains |
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
ICML
2010
IEEE
13 years 7 months ago
2010
IEEE
Inference in graphical models has emerged as a promising technique for planning. A recent approach to decision-theoretic planning in relational domains uses forward inference in d...
COGSCI
2010
13 years 6 months ago
2010
The contributions to this special issue on cognitive development collectively propose ways in which learning involves developing constraints that shape subsequent learning. A lear...
AAAI
2012
11 years 8 months ago
2012
This paper concerns learning and prediction with probabilistic models where the domain sizes of latent variables have no a priori upper-bound. Current approaches represent prior d...
HYBRID
1998
Springer
13 years 10 months ago
1998
Springer
We discuss properties of high order neurons in competitive learning. In such neurons, geometric shapes replace the role of classic `point' neurons in neural networks. Complex ...