28 search results - page 1 / 6 » Complexity of Probabilistic Planning under Average Rewards |
IJCAI
2001
13 years 5 months ago
2001
A general and expressive model of sequential decision making under uncertainty is provided by the Markov decision processes (MDPs) framework. Complex applications with very large ...
JAIR
2006
13 years 4 months ago
2006
A decision process in which rewards depend on history rather than merely on the current state is called a decision process with non-Markovian rewards (NMRDP). In decisiontheoretic...
CORR
1998
Springer
13 years 4 months ago
1998
Springer
We examine the computational complexity of testing and nding small plans in probabilistic planning domains with both at and propositional representations. The complexity of plan e...
ECP
1997
Springer
13 years 8 months ago
1997
Springer
A possibilistic approach of planning under uncertainty has been developed recently. It applies to problems in which the initial state is partially known and the actions have graded...
IROS
2006
IEEE
13 years 10 months ago
2006
IEEE
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...