There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data. However, in many settings the HDP-HMM's strict Markovian constraints...

Existing preference reasoning systems have been successful in simple domains. Broader success requires more natural and more expressive preference representations. This thesis develops a representation of logical preferences that combines numerical tradeoff ratios between partial outcome...

In many studies of market microstructure, theoretical analysis quickly becomes in tractable for all but the simplest stylized models. This thesis considers two alternative approaches, namely, the use of experiments with human subjects and simulations with intelligent agents, to address some of...