We present a dynamic programming approach for the solution of first-order Markov decisions processes. This technique uses an MDP whose dynamics is represented in a variant of the ...
Markov decision processes (MDPs) are a very popular tool for decision theoretic planning (DTP), partly because of the welldeveloped, expressive theory that includes effective solu...
We consider the average cost problem for partially observable Markov decision processes (POMDP) with finite state, observation, and control spaces. We prove that there exists an -...
The potentially catastrophic impact of a bioterrorist attack makes developing effective detection methods essential for public health. In the case of anthrax attack, a delay of ho...
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...