Anytime anyspace probabilistic inference

Fabio Tozeto Ramos, Fabio Gagliardi Cozman
2005 International Journal of Approximate Reasoning  
This paper investigates methods that balance time and space constraints against the quality of Bayesian network inferences--we explore the three-dimensional spectrum of "time · space · quality" trade-offs. The main result of our investigation is the adaptive conditioning algorithm, an inference algorithm that works by dividing a Bayesian network into sub-networks and processing each sub-network with a combination of exact and anytime strategies. The algorithm seeks a balanced synthesis of
more » ... ilistic techniques for bounded systems. Adaptive conditioning can produce inferences in situations that defy existing algorithms, and is particularly suited as a component of bounded agents and embedded devices.
doi:10.1016/j.ijar.2004.04.001 fatcat:lrvtscaumvbuhny56scwycpn4e