Reference documentation is an important source of information on API usage. Programmers, however, can easily overlook reference information because of its tedious nature, and because the information they seek can be buried among irrelevant or boiler-plate text. We propose to…

Authentication protocols aim to prevent agent impersonation: A is authenticated to B if B knows who A is. Many formal approaches have been used to verify authentication in distributed systems; however, although authentication is directly related to agent knowledge, it…

Positron emission tomography (PET) imaging is becoming increasingly popular for understanding brain function. This thesis addresses two problems related to PET images: binding potential (BP) computation and pairwise PET image registration. We first investigate the influence of several computational choices…

Modern information systems, consisting of an application server tier and a database tier, offer several consistency guarantees for accessing data where strong consistency is traded for better performance or higher availability. However, it is often not clear how an application…

Decision-making under uncertainty has become critical as autonomous and semi-autonomous agents become more ubiquitious in our society. These agents must deal with uncertainty and ambiguity from the environment and still perform desired tasks robustly. Partially observable Markov decision processes (POMDPs)…

Data are produced in large quantities and in various forms around the globe everyday. Researchers advance their research depending on the availability of necessary data and the discovery of them. As people's demand to manage the data grows, however, three…

Spoken dialogue systems are gaining popularity with improvements in speech recognition technologies. Dialogue systems have been modeled effectively using Partially observable Markov decision processes (POMDPs), achieving improvements in robustness. However, past research on POMDP-based dialogue systems usually assumes that the…

This dissertation addresses the problem of sequential decision making under uncertainty in large systems. The formalisms used to study this problem are fully and partially observable Markov Decision Processes (MDPs and POMDPs, respectively). The first contribution of this dissertation is…