360 search results - page 10 / 72 » Combining Learned Discrete and Continuous Action Models |
TROB
2010
14 years 7 months ago
2010
—To efficiently solve challenging motion-planning problems with dynamics, this paper proposes treating motion planning not just as a search problem in a continuous space but as ...
82
Voted
JMLR
2006
14 years 9 months ago
2006
We propose a novel approach to optimize Partially Observable Markov Decisions Processes (POMDPs) defined on continuous spaces. To date, most algorithms for model-based POMDPs are ...
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
We introduce new, efficient algorithms for value iteration with multiple reward functions and continuous state. We also give an algorithm for finding the set of all nondominated a...
ICCS
2005
Springer
15 years 3 months ago
2005
Springer
We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily ...
ICANNGA
2007
Springer
15 years 3 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...