312 search results - page 18 / 63 » Learning Partially Observable Deterministic Action Models |
ECML
2007
Springer
14 years 1 months ago
2007
Springer
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
ICRA
2007
IEEE
14 years 1 months ago
2007
IEEE
— While the Partially Observable Markov Decision Process (POMDP) provides a formal framework for the problem of robot control under uncertainty, it typically assumes a known and ...
ICCV
2009
IEEE
15 years 18 days ago
2009
IEEE
We use concepts from chaos theory in order to model
nonlinear dynamical systems that exhibit deterministic behavior.
Observed time series from such a system can be embedded
into...
TSMC
2008
13 years 6 months ago
2008
This paper explores the issues faced in creating a sys-4 tem that can learn tactical human behavior merely by observing5 a human perform the behavior in a simulation. More specific...
ICANN
2005
Springer
14 years 1 months ago
2005
Springer
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goaldirected imitation. The control architecture is b...