350 search results - page 11 / 70 » Complexity of Planning with Partial Observability |
AAAI
1997
13 years 10 months ago
1997
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
NIPS
2008
13 years 10 months ago
2008
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
MFCS
2010
Springer
13 years 7 months ago
2010
Springer
We study observation-based strategies for partially-observable Markov decision processes (POMDPs) with parity objectives. An observationbased strategy relies on partial information...
CORR
1998
Springer
13 years 8 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...
HICSS
2003
IEEE
14 years 2 months ago
2003
IEEE
We adopt the decision-theoretic principle of expected utility maximization as a paradigm for designing autonomous rational agents operating in multi-agent environments. We use the...