This thesis investigates an intelligent system that can in real time infer the course of action of a human opponent in a competitive environment. Such an achievement would indicate the possibility that machines can not only interpret human behavior as it happens, but also predict the future course of action that a human might take. This thesis first examines several different application of intention recognition, describes the approach of Template Based Interpretation (TBI), and details the process of creating an efficient and accurate intention recognition system. The domain chosen is chess. The system's objective was to discern the opponent's strategy. It is able to use the board positions and other relevant data of the current state to gain an understanding of the movement patterns of the opposition.

M.Sc. / Grid computing is a technology concerned with harvesting idle resources of geographically distributed and interconnected computers. It solves problems regarded as too complex or large to be solved by a single computer. Furthermore, economic grid computing is becoming the most dominant form of grid computing. It enables some form of payment to occur between resource producers and resource consumers in grid computing. Mobile devices and mobile telecommunication services, a relatively new field of technology, are rapidly increasing in popularity, size, strength and application. At the end of 2006, there were approximately 2.7 billion global active mobile users utilising mobile devices and mobile telecommunication services [Aho07]. At the end of 2007 this number had grown to 3.3 billion mobile users, more than half a billion additional mobile users in a period of one year [McN07]. With such large numbers, grid computing can benefit from the clustering of mobile devices forming a mobile grid computing model. However, there are many inherent disadvantages concerning mobile devices, such as low processing capabilities, unpredictable network connections and battery utilisation. Such hurdles must be addressed and solved if a mobile computing infrastructure or architecture is ever to be considered. This dissertation proposes the implementation of an economic mobile computing solution: Mobile Agents for Global Mobile Device Grid Infrastructure Enterprises, or MAGGIE. MAGGIE is concerned with harvesting idle mobile device resources by implementing the supply and demand economic model, aiming to create a healthy competitive economic market environment. MAGGIE implements agent and mobile agent technology to compensate for the hurdles introduced by mobile devices and mobile device software development platforms. It is targeted at both Sun Microsystems’s J2ME MIDP 2.0 and Microsoft’s .NET Compact Framework, enabling lower-end and higher-end mobile devices to contribute mobile computing services and resources for utilisation by other mobile device users. The primary goal of MAGGIE is to produce an architecture as generic as possible regarding the development and implementation of MAGGIE services. MAGGIE allows third-party application developers to seamlessly implement an array of MAGGIE services, without indepth prior knowledge of the architecture and technical aspects of MAGGIE. Finally, MAGGIE’s capabilities are demonstrated by implementing a distributed mobile chess service known as the MAGGIE Chess Service. The MAGGIE Chess Service enables a collection of distributed mobile devices in determining the best move originating from a chessboard position.

Tong Kwong-Bun. / Thesis submitted in: December 2002. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 77-[80]). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- An Overview --- p.1 / Chapter 1.2 --- Tree Search --- p.2 / Chapter 1.2.1 --- Minimax Algorithm --- p.2 / Chapter 1.2.2 --- The Alpha-Beta Algorithm --- p.4 / Chapter 1.2.3 --- Alpha-Beta Enhancements --- p.5 / Chapter 1.2.4 --- Selective Search --- p.9 / Chapter 1.3 --- Construction of Evaluation Function --- p.16 / Chapter 1.4 --- Contribution of the Thesis --- p.17 / Chapter 1.5 --- Structure of the Thesis --- p.19 / Chapter 2 --- The Probabilistic Forward Pruning Framework --- p.20 / Chapter 2.1 --- Introduction --- p.20 / Chapter 2.2 --- The Generalized Probabilistic Forward Cuts Heuristic --- p.21 / Chapter 2.3 --- The GPC Framework --- p.24 / Chapter 2.3.1 --- The Alpha-Beta Algorithm --- p.24 / Chapter 2.3.2 --- The NegaScout Algorithm --- p.25 / Chapter 2.3.3 --- The Memory-enhanced Test Algorithm --- p.27 / Chapter 2.4 --- Summary --- p.27 / Chapter 3 --- The Fast Probabilistic Forward Pruning Framework --- p.30 / Chapter 3.1 --- Introduction --- p.30 / Chapter 3.2 --- The Fast GPC Heuristic --- p.30 / Chapter 3.2.1 --- The Alpha-Beta algorithm --- p.32 / Chapter 3.2.2 --- The NegaScout algorithm --- p.32 / Chapter 3.2.3 --- The Memory-enhanced Test algorithm --- p.35 / Chapter 3.3 --- Performance Evaluation --- p.35 / Chapter 3.3.1 --- Determination of the Parameters --- p.35 / Chapter 3.3.2 --- Result of Experiments --- p.38 / Chapter 3.4 --- Summary --- p.42 / Chapter 4 --- The Node-Cutting Heuristic --- p.43 / Chapter 4.1 --- Introduction --- p.43 / Chapter 4.2 --- Move Ordering --- p.43 / Chapter 4.2.1 --- Quality of Move Ordering --- p.44 / Chapter 4.3 --- Node-Cutting Heuristic --- p.46 / Chapter 4.4 --- Performance Evaluation --- p.48 / Chapter 4.4.1 --- Determination of the Parameters --- p.48 / Chapter 4.4.2 --- Result of Experiments --- p.50 / Chapter 4.5 --- Summary --- p.55 / Chapter 5 --- The Integrated Strategy --- p.56 / Chapter 5.1 --- Introduction --- p.56 / Chapter 5.2 --- "Combination of GPC, FGPC and Node-Cutting Heuristic" --- p.56 / Chapter 5.3 --- Performance Evaluation --- p.58 / Chapter 5.4 --- Summary --- p.63 / Chapter 6 --- Conclusions and Future Works --- p.64 / Chapter 6.1 --- Conclusions --- p.64 / Chapter 6.2 --- Future Works --- p.65 / Chapter A --- Examples --- p.67 / Chapter B --- The Rules of Chinese Checkers --- p.73 / Chapter C --- Application to Chinese Checkers --- p.75 / Bibliography --- p.77