18 search results - page 2 / 4 » Approximate Probabilistic Constraints and Risk-Sensitive Opt... |
CORR
2010
Springer
13 years 5 months ago
2010
Springer
The success of probabilistic model checking for discrete-time Markov decision processes and continuous-time Markov chains has led to rich academic and industrial applications. The ...
VMCAI
2010
Springer
14 years 3 months ago
2010
Springer
This paper investigates relative precision and optimality of analyses for concurrent probabilistic systems. Aiming at the problem at the heart of probabilistic model checking ? com...
ATAL
2004
Springer
13 years 11 months ago
2004
Springer
Decentralized MDPs provide a powerful formal framework for planning in multi-agent systems, but the complexity of the model limits its usefulness. We study in this paper a class o...
TACAS
2007
Springer
13 years 12 months ago
2007
Springer
We study and provide efficient algorithms for multi-objective model checking problems for Markov Decision Processes (MDPs). Given an MDP, M, and given multiple linear-time (ω-regu...
UAI
2008
13 years 7 months ago
2008
Approximate linear programming (ALP) is an efficient approach to solving large factored Markov decision processes (MDPs). The main idea of the method is to approximate the optimal...