Comparison of model prediction against observed data is an investigative step used in cognitive modeling research for human-computer interaction. In this paper we describe compari...
As the hardware and software complexity grows, it is unlikely for the power management hardware/software to have a full observation of the entire system status. In this paper, we ...
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Bayesian networks are probabilistic graphical models widely employed in AI for the implementation of knowledge-based systems. Standard inference algorithms can update the beliefs a...
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...