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In this thesis we consider the task of catching a moving target with multiple pursuers, also known as the “Pursuit Game”, in which coordination among the pursuers is critical. Our testbed is inspired by the pursuit problem in video games, which require fast planning to guarantee fluid frame rates. We apply supervised machine learning methods to automatically derive efficient multi-agent pursuit strategies on rectangular grids. Learning is achieved by computing training data off-line and exploring the game tree on small problems. We also generalize the data to previously unseen and larger problems by learning robust pursuit policies, and run empirical comparisons between several sets of state features using a simple learning architecture. The empirical results show that 1) the application of learning across different maps can help improve game-play performance, especially on non-trivial maps against intelligent targets, and 2) simple heuristic works effectively on simple maps or less intelligent targets.

This paper is mainly based on Brown and Levinson’s negative politeness strategies and Mona Baker’s translation strategies to analyze how the translators of the Chinese novel, Honglou meng, employ these strategies to render honorifics and self-deprecatory expressions in Honglou meng from Chinese into English. It compares the two English translations and observes the translators’ tendencies in both translations. The findings suggest that David Hawkes’ translation is esthetically crafted language and more target-oriented, whereas Yang Hsien-yi and Glays Yang’s translation is not such natural-sounding English and more source-oriented. This paper also states that a comprehensive theoretical frame in this area is yet to be established.

The exploration of oceans and sea beds is being made increasingly possible through the development of Autonomous Underwater Vehicles (AUVs). This is an activity that concerns the marine community and it must confront the existence of notable challenges. These include, for example, mining minerals, inspecting pipeline and mapping oceans, sampling in contaminated water. Also, there has been another growing interest for security forces in precluding submarines or intruders from a beach or harbour entrance as well as hunting shallow water mines. However, an automatic detecting and tracking system is the first and foremost element for an AUV or an aqueous surveillance network. Since accurate surrounding information is essential in order to manoeuvre the AUV efficiently and economically, while corrupt information can jeopardize an entire mission. By extracting the space information form sensors, an AUV can achieve the localisation and mapping which are currently two primary concerns in the robotics research. Meanwhile, such information will provide a fundament of protection for surface vessels or troops, harbour infrastructure and oil plant against the enemy and terrorism. Acoustic sensors are commonly used to detect and position underwater obstacles, suspicious objects or to map the surroundings because sound waves can propagate more appreciable distances than electromagnetic and optical energy in the water. The measurements from these sensors, however, are always bound up with noises and errors. Various underwater activities may further pollute sound signals and then threaten the AUV navigation process. To simplify the detection procedure, some researchers make use of acoustic beacons or apparent obstructions (such as rocks, concrete walls) because they have distinctive characteristics. Point or line features are extracted from the acoustic signals or images for localization and mapping purposes. The long propagation range of sound waves can present new problems when acoustic sensors operate in confined environments, such as water tanks, rivers and harbours. The multiple reflections will be recorded by the sensor and result in false alarms. Furthermore, with advances in manufacturing techniques, the downsizing in marine explosive ordnances is progressing significantly, making it more difficult to discriminate between surface reflections and explosive ordnances. Finally, under the consideration of cost effectiveness, a mechanically scanned sonar has been introduced for the AUV in this research. However, the sensor beam cannot cover a large region simultaneously and a moving object may be distorted in the acoustic image because of the relatively low scanning speed. Due to such distortions in the data flows, objects may be indistinguishable from random noise or reverberation in acoustic images. The research presented here addresses the afore-mentioned problems relating to the theme of automatic detection from acoustic images. It is concerned with the detection and tracking of small underwater objects in order to protect autonomous underwater vehicles using sonar (SOund Navigation and Range). In the present study, these vehicles operated in laboratory water tanks or natural river environments. This research made use of self provided analytical studies that differentiated between reverberation and real object echoes. Detections were achieved automatically by using signal and image processing techniques. This research consists of three important and linked strategies. Firstly, a simple and fast reverberation suppression filter was provided, based on the understanding of the mechanism of the sonar sensor. Secondly, a robust detection system was developed to perceive small suspended obstacles in the water. Thirdly and finally, arc features were successfully extracted from the acoustic images and mathematical maps were generated from those features. The majority of experiments were derived from the elliptical water tank and the River Torrens, Adelaide, South Australia. For this project, a sequence of sonar images was taken from the same sonar location in the elliptical water tank. Further, a sequence of sonar images was taken from a sequence of sonar locations in the natural river. They provided different data sets for the assessment and evaluation of self developed algorithms. Results shown in this thesis confirm the favourable outcomes of the investigation and applied methodology. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1454839 / Thesis (M.Eng.Sc.) -- University of Adelaide, School of Mechanical Engineering, 2010

Thesis (Ph. D.)--University of Texas at Austin, 2008. / Vita. Includes bibliographical references.

Thesis (M.S.)--Air Force Institute of Technology, 2008. / AFIT/GOR/ENS/08-22. "March 2008." Title from title page of PDF document (viewed on: Jan. 5, 2009). Includes bibliographical references.

Thesis (M.S.)--Auburn University, 2008. / Abstract. Vita. Includes bibliographical references (p. 36-37).

Thesis (M.S. in Management of Technology)--Vanderbilt University, May 2005. / Title from title screen. Includes bibliographical references.

Thesis--PlanB (M.S.)--University of Wisconsin--Stout, 1999. / Includes bibliographical references.

Thesis (Ph. D.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2007. / Includes bibliographical references (p. 113-119).