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Learning agents often find themselves in environments in which rare significant events occur independently of their current choice of action. Traditional reinforcement learning algorithms sample events according to their natural probability of occurring, and therefore tend to exhibit slow convergence and high variance in such environments. In this thesis, we assume that learning is done in a simulated environment in which the probability of these rare events can be artificially altered. We present novel algorithms for both policy evaluation and control, using both tabular and function approximation representations of the value function. These algorithms automatically tune the rare event probabilities to minimize the variance and use importance sampling to correct for changes in the dynamics. We prove that these algorithms converge, provide an analysis of their bias and variance, and demonstrate their utility in a number of domains, including a large network planning task.

Thesis (PhD)--University of South Australia, 1999

Plasma polymerisation (PP) is an emerging processing technology with immense potential for future industrial applications, which is increasingly being used for the fabrication of functional coatings on polymeric substrates. In this technique, the solid polymeric film is directly deposited onto the substrate surface to create a new surface of very interesting and unique properties. PP utilizes gas phase chemistries in low pressure environment to produce well-defined high quality films in controllable and tunable fashion. A major advantage of this process is that it is an environmental safety technique and strategically superior compared to other thin film deposition techniques such as spin coating and spray coating. In eneral, the quality of the plasma polymer film can be controlled, precisely and reproducible. However, mechanism of the coating under plasma polymerisation is complex and has not yet been completely understood. / Thesis (PhD)--University of South Australia, 1999

vii, 343 leaves : diags. tables. ; 30 cm / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Statistics, 1978

Thesis (PhD)--University of South Australia, 1999

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (M.A.)--University of Toronto, 2005.

Thesis (Ph. D.) -- University of Newcastle, 2004. / School of Engineering. Discipline of Civil, Surveying and Environmental Engineering. Includes bibliographical references (leaves 205 - 217). Also available online.