Rockfish of the genus Sebastes are important components of Oregon reef communities. I examined patterns of age and growth in young-of-year rockfish across two nested spatial scales – local and regional – along the Oregon coast. Using otolith microstructural examination, I examined the relative importance of local versus regional factors...
The thesis focuses on model-based approximation methods for reinforcement
learning with large scale applications such as combinatorial optimization problems.
First, the thesis proposes two new model-based methods to stablize the
value–function approximation for reinforcement learning. The first one is the
BFBP algorithm, a batch-like reinforcement learning process which iterates between...
Building intelligent computer assistants has been a long-cherished goal of AI. Many intelligent assistant systems were built and fine-tuned to specific application domains. In this work, we develop a general model of assistance that combines three powerful ideas: decision theory, hierarchical task models and probabilistic relational languages. We use the...
The functioning of marine habitats needs to be understood in the context of the ecological relationships and associations between organisms and the physical and biogenic environment they inhabit. Thus, it becomes important to explore and define habitat features which contribute to these relationships and which are important in the life...
Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
Coordination in large multiagent systems in order to achieve a system level goal is a critical challenge. Given the agents' intention to cooperate, there is no guarantee that the agent actions will lead to good system objective especially when the system becomes large. One of the primary difficulties in such...
How can an agent generalize its knowledge to new circumstances? To learn
effectively an agent acting in a sequential decision problem must make intelligent action selection choices based on its available knowledge. This dissertation focuses on Bayesian methods of representing learned knowledge and develops novel algorithms that exploit the represented...
The success of NIKE, Inc. is deemed miracle by professionals on both Wall
Street and Madison Avenue. Research done in the past tends to credit the growth
of NIKE, Inc. to its marketing strategies. By placing the achievement of the
company in the postmodern context, this study analyzes the cultural...
We have recently reported that cell-penetrating peptides (CPPs) and novel chimeric peptides containing CPP (referred as
B peptide) and muscle-targeting peptide (referred as MSP) motifs significantly improve the systemic exon-skipping activity
of morpholino phosphorodiamidate oligomers (PMOs) in dystrophin-deficient mdx mice. In the present study, the general
mechanistic significance of the...
This thesis considers the problem in which a teacher is interested in teaching action policies to computer agents for sequential decision making. The vast majority of policy
learning algorithms o er teachers little flexibility in how policies are taught. In particular,
one of two learning modes is typically considered: 1)...