16 search results - page 1 / 4 » Probabilistic Planning with Nonlinear Utility Functions |
AIPS
2006
13 years 6 months ago
2006
Researchers often express probabilistic planning problems as Markov decision process models and then maximize the expected total reward. However, it is often rational to maximize ...
AAAI
2006
13 years 6 months ago
2006
We study how to find plans that maximize the expected total utility for a given MDP, a planning objective that is important for decision making in high-stakes domains. The optimal...
IJRR
2010
13 years 1 months ago
2010
Advances in the direct computation of Lyapunov functions using convex optimization make it possible to efficiently evaluate regions of attraction for smooth nonlinear systems. Her...
KR
1994
Springer
13 years 8 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...
ATAL
2010
Springer
13 years 5 months ago
2010
Springer
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...