Sciweavers

Share
30 search results - page 1 / 6
» Complexity of Probabilistic Planning under Average Rewards
Sort
View
IJCAI
2001
9 years 2 months ago
Complexity of Probabilistic Planning under Average Rewards
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 ...
Jussi Rintanen
JAIR
2006
157views more  JAIR 2006»
9 years 1 months ago
Decision-Theoretic Planning with non-Markovian Rewards
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...
Sylvie Thiébaux, Charles Gretton, John K. S...
AAAI
2015
3 years 9 months ago
CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot
In order to be fully robust and responsive to a dynamically changing real-world environment, intelligent robots will need to engage in a variety of simultaneous reasoning modaliti...
Shiqi Zhang, Peter Stone
CORR
1998
Springer
135views Education» more  CORR 1998»
9 years 28 days ago
The Computational Complexity of Probabilistic Planning
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...
Michael L. Littman, Judy Goldsmith, Martin Mundhen...
ECP
1997
Springer
125views Robotics» more  ECP 1997»
9 years 5 months ago
Possibilistic Planning: Representation and Complexity
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...
Célia da Costa Pereira, Frédé...
books