85 search results - page 3 / 17 » Solving Stochastic Planning Problems with Large State and Ac... |
JAIR
2008
13 years 7 months ago
2008
Probabilistic planning problems are typically modeled as a Markov Decision Process (MDP). MDPs, while an otherwise expressive model, allow only for sequential, non-durative action...
AIPS
1994
13 years 8 months ago
1994
In this work we present an approach to solving time-critical decision-making problems by taking advantage of domain structure to expand the amountof time available for processing ...
AAAI
2008
13 years 9 months ago
2008
This paper investigates the impact of symbolic search for solving domain-independent action planning problems with binary decision diagrams (BDDs). Polynomial upper and exponential...
ICTAI
2000
IEEE
13 years 11 months ago
2000
IEEE
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
ICTAI
2005
IEEE
14 years 1 months ago
2005
IEEE
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...