Leung Shi Sing. / "Architecture Department, Chinese University of Hong Kong, Master of Architecture Programme 2007-2008, design report." / Includes bibliographical references (leaves 62). / Chapter 01 --- BACKGROUND --- p.1-6 / Chapter 02 --- STUDIES OF SERVICE SPACES --- p.7-19 / Chapter 03 --- DESIGN DEVELOPMENT --- p.20-30 / Chapter 04 --- FINAL DESIGN --- p.31-61 / Chapter 04.1 --- TYPE 1 ´Ø UNIT --- p.32-34 / Chapter 04.2 --- TYPE 2 ´Ø GROUP --- p.35-42 / Chapter 04.3 --- TYPE 3 ´Ø COMMUNITY --- p.43-61 / Chapter 05 --- BIBLIOGRAPHY --- p.62

Freight transportation is a significant component of the nation’s economy. However, the augmented volume of the freight movements contributed to continuously increasing congestion on the urban road networks, that affects the timeliness and reliability of freight transportation. In addition, congestion has a negative impact on the transit operations as well. Various studies conducted on multi-modal corridors recognized the importance of the simultaneous performance of freight and transit operations. Thus, Intelligent Transportation System (ITS) components, such as Freight Signal Priority (FSP) and Transit Signal Priority (TSP), present traffic operations strategies "shaped" to give priority, reduce delay and travel time, and overall improve the performance of freight and transit movements, respectively. The primary objective of the thesis refers to evaluate possible improvements in freight mobility, while sustaining good transit services and minimizing congestion on the multi-modal corridor, through simultaneous implementation of the FSP and the TSP. The effectiveness of the newly established criteria was evaluated through real-world case study on a micro-simulation platform. The results showed significant improvements on all the vehicle movements. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

???Agent-based systems are one of the most vibrant and important areas of research and development to have emerged in information technology in the 1990s??? (Luck et al. 2003). The use of agents as a metaphor for designing and constructing software systems represents an innovative movement in the field of software engineering: ???Agent- Oriented Software Engineering (AOSE)??? (Lind 2000; Luck et al. 2003). This research contributes to the evolution of AOSE by proposing a comprehensive ontology-based methodology for the analysis and design of Multi-Agent Systems (MAS). The methodology is named MOBMAS, which stands for ???Methodology for Ontology-Based MASs???. A major improvement of MOBMAS over the existing agentoriented MAS development methodologies is its explicit and extensive support for ontology-based MAS development. Ontologies have been widely acknowledged for their significant benefits to interoperability, reusability, MAS development activities (such as system analysis and agent knowledge modelling) and MAS operation (such as agent communication and reasoning). Recognising these desirable ontology???s benefits, MOBMAS endeavours to identify and implement the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In so doing, MOBMAS has exploited ontologies to enhance its MAS development process and MAS development product with various strengths. These strengths include those ontology???s benefits listed above, and those additional benefits uncovered by MOBMAS, e.g. support for verification and validation, extendibility, maintainability and reliability. Compared to the numerous existing agent-oriented methodologies, MOBMAS is the first that explicitly and extensively investigates the diverse potential advantages of ontologies in MAS development, and which is able to implement these potential advantages via an ontology-based MAS development process and a set of ontology-based MAS model definitions. Another major contribution of MOBMAS to the field of AOSE is its ability to address all key concerns of MAS development in one methodological framework. The methodology provides support for a comprehensive list of methodological requirements, which are important to agent-oriented analysis and design, but which may not be wellsupported by the current methodologies. These methodological requirements were identified and validated by this research from three sources: the existing agent-oriented methodologies, the existing evaluation frameworks for agent-oriented methodologies and conventional system development methodologies, and a survey of practitioners and researchers in the field of AOSE. MOBMAS supports the identified methodological requirements by combining the strengths of the existing agent-oriented methodologies (i.e. by reusing and enhancing the various strong techniques and model definitions of the existing methodologies where appropriate), and by proposing new techniques and model definitions where necessary. The process of developing MOBMAS consisted of three sequential research activities. The first activity identified and validated a list of methodological requirements for an Agent Oriented Software Engineering methodology as mentioned above. The second research activity developed MOBMAS by specifying a development process, a set of techniques and a set of model definitions for supporting the identified methodological requirements. The final research activity evaluated and refined MOBMAS by collecting expert reviews on the methodology, using the methodology on an application and conducting a feature analysis of the methodology.

This thesis illustrates and evaluates a generic adaptive tutoring environment based on the theory of cognitive skill acquisition. The theory concerns acquiring problem-solving abilities in intellectual tasks, and emphasises the learning benefits of providing multiple examples and encouraging students to recognize and study their common structure. The system teaches by presenting side-by-side examples and providing devices to highlight their structural components. The purpose of the design is to assist the process of generalisation and reduce mapping by surface features, allowing students to apply their newly gained knowledge to different sets of problems. The study describes the development of Structural Example-based Adaptive Tutoring System (SEATS), which uses a simple adaptive engine and emphasises the structures of side-by-side examples to encourage students to compare them. / thesis (PhD)--University of South Australia, 2001.

Providing a logical characterisation of rational agent reasoning has been a long standing challenge in artificial intelligence (AI) research. It is a challenge that is not only of interest for the construction of AI agents, but is of equal importance in the modelling of agent behaviour. The goal of this thesis is to contribute to the formalisation of agent reasoning by showing that the computational limitations of agents is a vital component of modelling rational behaviour. To achieve this aim, both motivational and formal aspects of resource-bounded agents are examined. It is a central argument of this thesis that accounting for computational limitations is critical to the success of agent reasoning, yet has received only limited attention from the broader research community. Consequently, an important contribution of this thesis is in its advancing of motivational arguments in support of the need to account for computational limitations in agent reasoning research. As a natural progression from the motivational arguments, the majority of this thesis is devoted to an examination of propositional approximate logics. These logics represent a step towards the development of resource-bounded agents, but are also applicable to other areas of automated reasoning. This thesis makes a number of contributions in mapping the space of approximate logics. In particular, it draws a connection between approximate logics and knowledge compilation, by developing an approximate knowledge compilation method based on Cadoli and Schaerf??s S-3 family of approximate logics. This method allows for the incremental compilation of a knowledge base, thus reducing the need for a costly recompilation process. Furthermore, each approximate compilation has well-defined logical properties due to its correspondence to a particular S-3 logic. Important contributions are also made in the examination of approximate logics for clausal reasoning. Clausal reasoning is of particular interest due to the efficiency of modern clausal satisfiability solvers and the related research into problem hardness. In particular, Finger's Logics of Limited Bivalence are shown to be applicable to clausal reasoning. This is subsequently shown to logically characterise the behaviour of the well-known DPLL algorithm for determining boolean satisfiability, when subjected to restricted branching.

???Agent-based systems are one of the most vibrant and important areas of research and development to have emerged in information technology in the 1990s??? (Luck et al. 2003). The use of agents as a metaphor for designing and constructing software systems represents an innovative movement in the field of software engineering: ???Agent- Oriented Software Engineering (AOSE)??? (Lind 2000; Luck et al. 2003). This research contributes to the evolution of AOSE by proposing a comprehensive ontology-based methodology for the analysis and design of Multi-Agent Systems (MAS). The methodology is named MOBMAS, which stands for ???Methodology for Ontology-Based MASs???. A major improvement of MOBMAS over the existing agentoriented MAS development methodologies is its explicit and extensive support for ontology-based MAS development. Ontologies have been widely acknowledged for their significant benefits to interoperability, reusability, MAS development activities (such as system analysis and agent knowledge modelling) and MAS operation (such as agent communication and reasoning). Recognising these desirable ontology???s benefits, MOBMAS endeavours to identify and implement the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In so doing, MOBMAS has exploited ontologies to enhance its MAS development process and MAS development product with various strengths. These strengths include those ontology???s benefits listed above, and those additional benefits uncovered by MOBMAS, e.g. support for verification and validation, extendibility, maintainability and reliability. Compared to the numerous existing agent-oriented methodologies, MOBMAS is the first that explicitly and extensively investigates the diverse potential advantages of ontologies in MAS development, and which is able to implement these potential advantages via an ontology-based MAS development process and a set of ontology-based MAS model definitions. Another major contribution of MOBMAS to the field of AOSE is its ability to address all key concerns of MAS development in one methodological framework. The methodology provides support for a comprehensive list of methodological requirements, which are important to agent-oriented analysis and design, but which may not be wellsupported by the current methodologies. These methodological requirements were identified and validated by this research from three sources: the existing agent-oriented methodologies, the existing evaluation frameworks for agent-oriented methodologies and conventional system development methodologies, and a survey of practitioners and researchers in the field of AOSE. MOBMAS supports the identified methodological requirements by combining the strengths of the existing agent-oriented methodologies (i.e. by reusing and enhancing the various strong techniques and model definitions of the existing methodologies where appropriate), and by proposing new techniques and model definitions where necessary. The process of developing MOBMAS consisted of three sequential research activities. The first activity identified and validated a list of methodological requirements for an Agent Oriented Software Engineering methodology as mentioned above. The second research activity developed MOBMAS by specifying a development process, a set of techniques and a set of model definitions for supporting the identified methodological requirements. The final research activity evaluated and refined MOBMAS by collecting expert reviews on the methodology, using the methodology on an application and conducting a feature analysis of the methodology.

???Agent-based systems are one of the most vibrant and important areas of research and development to have emerged in information technology in the 1990s??? (Luck et al. 2003). The use of agents as a metaphor for designing and constructing software systems represents an innovative movement in the field of software engineering: ???Agent- Oriented Software Engineering (AOSE)??? (Lind 2000; Luck et al. 2003). This research contributes to the evolution of AOSE by proposing a comprehensive ontology-based methodology for the analysis and design of Multi-Agent Systems (MAS). The methodology is named MOBMAS, which stands for ???Methodology for Ontology-Based MASs???. A major improvement of MOBMAS over the existing agentoriented MAS development methodologies is its explicit and extensive support for ontology-based MAS development. Ontologies have been widely acknowledged for their significant benefits to interoperability, reusability, MAS development activities (such as system analysis and agent knowledge modelling) and MAS operation (such as agent communication and reasoning). Recognising these desirable ontology???s benefits, MOBMAS endeavours to identify and implement the various ways in which ontologies can be used in the MAS development process and integrated into the MAS model definitions. In so doing, MOBMAS has exploited ontologies to enhance its MAS development process and MAS development product with various strengths. These strengths include those ontology???s benefits listed above, and those additional benefits uncovered by MOBMAS, e.g. support for verification and validation, extendibility, maintainability and reliability. Compared to the numerous existing agent-oriented methodologies, MOBMAS is the first that explicitly and extensively investigates the diverse potential advantages of ontologies in MAS development, and which is able to implement these potential advantages via an ontology-based MAS development process and a set of ontology-based MAS model definitions. Another major contribution of MOBMAS to the field of AOSE is its ability to address all key concerns of MAS development in one methodological framework. The methodology provides support for a comprehensive list of methodological requirements, which are important to agent-oriented analysis and design, but which may not be wellsupported by the current methodologies. These methodological requirements were identified and validated by this research from three sources: the existing agent-oriented methodologies, the existing evaluation frameworks for agent-oriented methodologies and conventional system development methodologies, and a survey of practitioners and researchers in the field of AOSE. MOBMAS supports the identified methodological requirements by combining the strengths of the existing agent-oriented methodologies (i.e. by reusing and enhancing the various strong techniques and model definitions of the existing methodologies where appropriate), and by proposing new techniques and model definitions where necessary. The process of developing MOBMAS consisted of three sequential research activities. The first activity identified and validated a list of methodological requirements for an Agent Oriented Software Engineering methodology as mentioned above. The second research activity developed MOBMAS by specifying a development process, a set of techniques and a set of model definitions for supporting the identified methodological requirements. The final research activity evaluated and refined MOBMAS by collecting expert reviews on the methodology, using the methodology on an application and conducting a feature analysis of the methodology.

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

The goal of the commodity expert project was to develop a prototype program that would act as an intelligent assistant to a commodity market analyst. Since expert analysis must deal with very large, yet incomplete, data bases of unreliable facts about a complex world, the project would stringently test the applicability of Artificial Intelligence techniques. After a significant effort however, I am forced to the conclusion that an intelligent, real-world system of the kind envisioned is currently out of reach. Some of the difficulties were due to the size and complexity of the domain. As its true scale became evident, the available resources progressively appeared less adequate. The representation and reasoning problems that arose were persistently difficult and fundamental work is needed before the tools will be sufficient to engineer truly intelligent assistants. Despite these difficulties, perhaps even because of them, much can be learned from the project. To assist future applications projects, I explain in this report some of the reasons for the negative result, and also describe some positive ideas that were gained along the way. In doing so, I hope to convey the respect I have developed for the complexity of real-world domains, and the difficulty of describing the ways experts deal them.

The buckling of compressively-loaded members is one of the most important factors limiting the overall strength and stability of a structure. I have developed novel techniques for using active control to wiggle a structural element in such a way that buckling is prevented. I present the results of analysis, simulation, and experimentation to show that buckling can be prevented through computer-controlled adjustment of dynamical behavior.sI have constructed a small-scale railroad-style truss bridge that contains compressive members that actively resist buckling through the use of piezo-electric actuators. I have also constructed a prototype actively controlled column in which the control forces are applied by tendons, as well as a composite steel column that incorporates piezo-ceramic actuators that are used to counteract buckling. Active control of buckling allows this composite column to support 5.6 times more load than would otherwise be possible.sThese techniques promise to lead to intelligent physical structures that are both stronger and lighter than would otherwise be possible.