45 search results - page 7 / 9 » Formal models and algorithms for decentralized decision maki... |
AAAI
2008
13 years 8 months ago
2008
Partially Observable Markov Decision Processes have been studied widely as a model for decision making under uncertainty, and a number of methods have been developed to find the s...
EMO
2009
Springer
14 years 10 days ago
2009
Springer
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...
IJCAI
2007
13 years 7 months ago
2007
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
ATAL
2008
Springer
13 years 7 months ago
2008
Springer
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute an expressive framework for multiagent planning under uncertainty, but solving them is provabl...
ICMLA
2009
13 years 3 months ago
2009
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...