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IJRR
2008
101views more  IJRR 2008»
14 years 9 months ago
Motion Planning Under Uncertainty for Image-guided Medical Needle Steering
We develop a new motion planning algorithm for a variant of a Dubins car with binary left/right steering and apply it to steerable needles, a new class of flexible beveltip medica...
Ron Alterovitz, Michael S. Branicky, Kenneth Y. Go...
ICRA
2010
IEEE
163views Robotics» more  ICRA 2010»
14 years 8 months ago
Exploiting domain knowledge in planning for uncertain robot systems modeled as POMDPs
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...
ICTAI
2009
IEEE
14 years 7 months ago
TiMDPpoly: An Improved Method for Solving Time-Dependent MDPs
We introduce TiMDPpoly, an algorithm designed to solve planning problems with durative actions, under probabilistic uncertainty, in a non-stationary, continuous-time context. Miss...
Emmanuel Rachelson, Patrick Fabiani, Fréd&e...
PRIMA
2007
Springer
15 years 3 months ago
Multiagent Planning with Trembling-Hand Perfect Equilibrium in Multiagent POMDPs
Multiagent Partially Observable Markov Decision Processes are a popular model of multiagent systems with uncertainty. Since the computational cost for finding an optimal joint pol...
Yuichi Yabu, Makoto Yokoo, Atsushi Iwasaki
ECML
2007
Springer
15 years 3 months ago
Policy Gradient Critics
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 ...
Daan Wierstra, Jürgen Schmidhuber