85 search results - page 7 / 17 » Solving Stochastic Planning Problems with Large State and Ac... |
IAT
2005
IEEE
14 years 1 months ago
2005
IEEE
Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
VALUETOOLS
2006
ACM
14 years 1 months ago
2006
ACM
Min-max functions are dynamic programming operators of zero-sum deterministic games with finite state and action spaces. The problem of computing the linear growth rate of the or...
IJCAI
2001
13 years 8 months ago
2001
We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
AAAI
2011
12 years 7 months ago
2011
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
AI
2000
Springer
13 years 7 months ago
2000
Springer
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...