280 search results - page 7 / 56 » Planning for Markov Decision Processes with Sparse Stochasti... |
KR
1994
Springer
15 years 1 months ago
1994
Springer
Probabilistic AI planning methods that minimize expected execution cost have a neutral attitude towards risk. We demonstrate how one can transform planning problems for risk-sensi...
IJCAI
2007
14 years 11 months ago
2007
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
SODA
2010
ACM
15 years 7 months ago
2010
ACM
We study the computational complexity of some central analysis problems for One-Counter Markov Decision Processes (OC-MDPs), a class of finitely-presented, countable-state MDPs. O...
IJCAI
2007
14 years 11 months ago
2007
Agents often have to construct plans that obey deadlines or, more generally, resource limits for real-valued resources whose consumption can only be characterized by probability d...