85 search results - page 10 / 17 » Solving Stochastic Planning Problems with Large State and Ac... |
ASMTA
2008
Springer
13 years 9 months ago
2008
Springer
The solution of continuous and discrete-time Markovian models is still challenging mainly when we model large complex systems, for example, to obtain performance indexes of paralle...
AAAI
2000
13 years 8 months ago
2000
Reinforcement learning (RL) can be impractical for many high dimensional problems because of the computational cost of doing stochastic search in large state spaces. We propose a ...
JAIR
2006
13 years 7 months ago
2006
Fast Downward is a classical planning system based on heuristic search. It can deal with general deterministic planning problems encoded in the propositional fragment of PDDL2.2, ...
PKDD
2009
Springer
14 years 2 months ago
2009
Springer
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
HAPTICS
2008
IEEE
13 years 8 months ago
2008
IEEE
The well known property of haptic interaction is the high refresh rate of the haptic loop that is necessary for the stability of the interaction. Therefore, only simple computation...