67 search results - page 2 / 14 » Learning predictive state representations using non-blind po... |
ICMLA
2008
13 years 6 months ago
2008
Learning by imitation has shown to be a powerful paradigm for automated learning in autonomous robots. This paper presents a general framework of learning by imitation for stochas...
IJCAI
2003
13 years 6 months ago
2003
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
ICML
2009
IEEE
14 years 6 months ago
2009
IEEE
We consider the problem of estimating the policy gradient in Partially Observable Markov Decision Processes (POMDPs) with a special class of policies that are based on Predictive ...
ATAL
2008
Springer
13 years 7 months ago
2008
Springer
Predictive state representations (PSRs) are models that represent the state of a dynamical system as a set of predictions about future events. The existing work with PSRs focuses ...
NIPS
2001
13 years 6 months ago
2001
We show that states of a dynamical system can be usefully represented by multi-step, action-conditional predictions of future observations. State representations that are grounded...