Anytime anyspace probabilistic inference

F RAMOS
2004 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/s0888-613x(04)00047-7 fatcat:yu4uqhddarcodfum3knugvam3i