The Saskatchewan farm sector is a dynamic system that is faced with the reality of farm consolidation and other structural adjustments. While structural adjustment may result in increased productivity at the farm-level, the declining farm population has a direct impact on rural regions. Given the economic difficulties now inherent in many rural regions, there has never been a more important time to improve our understanding of the structural dynamics of the farm sector. <p> By utilizing agent-based methods, competition that exists between farm households in land markets is modelled in a dynamic framework. By modeling land markets in this manner, structural adjustments that occur due to the re-allocation of land among farm household becomes endogenous to the model. The farming simulation was validated by evaluating its ability to replicate actual structural shifts that occurred during the period of 1960-2000. The results obtained from the simulation were found to mirror historic shifts, which gives the author confidence that the parsimonious assumptions made are robust, yet still characteristic of farm level behaviour in the region. Other scenarios were simulated in order to estimate a counterfactual structural evolution of the modelled region, in the absence of government stabilization and support programs. Significant deviations are observed between the base and zero transfer scenarios with regards to the consolidation of farm assets among a declining number of farm households. Most significantly, the decline in farm numbers accelerated significantly in the late 1980s in the zero transfer scenario compared to the base simulations. <p>The application of an agent-based framework allowed for the study of regional structure with an emphasis on the behaviour and actions of the primary decisions makers within the system. While structural change is driven by a number of factors, the ability of a farm household to fully employ their labour resource was an important factor in the simulations. This contrasts with the finding that productive efficiency, and purchasing and market power at the farm level is not a necessary condition for the observed consolidation of farm assets.

The Saskatchewan farm sector is a dynamic system that is faced with the reality of farm consolidation and other structural adjustments. While structural adjustment may result in increased productivity at the farm-level, the declining farm population has a direct impact on rural regions. Given the economic difficulties now inherent in many rural regions, there has never been a more important time to improve our understanding of the structural dynamics of the farm sector. <p> By utilizing agent-based methods, competition that exists between farm households in land markets is modelled in a dynamic framework. By modeling land markets in this manner, structural adjustments that occur due to the re-allocation of land among farm household becomes endogenous to the model. The farming simulation was validated by evaluating its ability to replicate actual structural shifts that occurred during the period of 1960-2000. The results obtained from the simulation were found to mirror historic shifts, which gives the author confidence that the parsimonious assumptions made are robust, yet still characteristic of farm level behaviour in the region. Other scenarios were simulated in order to estimate a counterfactual structural evolution of the modelled region, in the absence of government stabilization and support programs. Significant deviations are observed between the base and zero transfer scenarios with regards to the consolidation of farm assets among a declining number of farm households. Most significantly, the decline in farm numbers accelerated significantly in the late 1980s in the zero transfer scenario compared to the base simulations. <p>The application of an agent-based framework allowed for the study of regional structure with an emphasis on the behaviour and actions of the primary decisions makers within the system. While structural change is driven by a number of factors, the ability of a farm household to fully employ their labour resource was an important factor in the simulations. This contrasts with the finding that productive efficiency, and purchasing and market power at the farm level is not a necessary condition for the observed consolidation of farm assets.

Modern robotics demonstrates the reality of near sci-fi solutions regularly. Swarms of interconnected robotic agents have been proven to have benefits in scalability, robustness, and efficiency. In communication restricted environments, such teams of robots are often required to support their own navigation, planning, and decision making processes, through use of onboard processors and collaboration. Example scenarios that exhibit restriction include unmanned underwater surveys and robots operating in indoor or remote environments without cloud connectivity. We begin this thesis by discussing multi-agent state estimation and it's observability properties, specifically for the case of an agent-to-agent range measurement system. For this case, inspired by navigation requirements underwater, we derive several conditions under which the system's state is guaranteed to be locally weakly observable. Ensuring a state is observable is necessary to maintain an estimate of it via filters, thus observability is required to support higher level navigation and planning. We conclude this section by creating an observability-based planner to control a subset of the agents' inputs. For the next contribution, we discuss scalability for coverage maximizing path planners. Typically planning for many individual robots incurs significant computational complexity which increases exponentially with the number of agents, this is often exacerbated when the objective function is collaborative as in coverage optimization. To maintain feasibility while planning for a large team of robots, we call upon a powerful relation from combinatorics which utilizes the greedy selection algorithm and a matroid condition to create an efficient planner that maintains a fixed performance ratio when compared to the optimal path. We then introduce a motivating example of autonomously assisted search and rescues using multiple aerial agents, and derive planners and models to suit the application. The framework begins by estimating the likely locations of a lost person through a Monte Carlo simulation, yielding a heatmap covering the area of interest. The heatmap is then used in combination with parametrized agent trajectories and a machine learning optimization algorithm to maximize the search efficiency. The search and rescues use case provides an excellent computational testbed for the final portion of the work. We close by discussing a computation architecture to support multi-agent system autonomy. Modern robotic autonomy results, especially computer vision and machine learning algorithms, often require large amounts of processing to yield quality results. With general purpose computing devices reaching a progression barrier, one that is not expected to be solved in the near term, increasingly devices must be designed with their end purposes in mind. To better support autonomy in multi-agent systems, we propose to use a distributed cluster of embedded processors which allows the sharing of computation and storage resources among the component members with minimal communication overhead. Our proposed architecture is composed of mature softwares already well-known in the robotics community, Kubernetes and the robot operating system, allowing ease of use and interoperability with existing algorithms. / Doctor of Philosophy / The traditional approach of robotics typically uses a single large platform capable of accomplishing all tasks assigned to it. However, it has been discovered that deploying multiple smaller platforms, each with their own processor and specific expertise, can have massive performance benefits compared to previous approaches. This development has been driven largely by readily available computing and mobility hardware. Termed as multi-agent systems, they can excel in areas that benefit from multiple perspectives, simultaneous task execution, and redundancy. In addition, planning algorithms developed for previous approaches often can map well onto multi-agent systems, provided there is adequate computational support. In cases where network or cloud connectivity is limited, teams of agents must use their own processors and sensors to make decisions and communicate. However, often an individual agent's computing hardware is limited in mass or size, thus limiting it's processing capabilities. In this work we will first discuss several multi-agent system algorithms, starting with estimation and navigation and ending with area search. We then conclude the work by proposing a novel architecture designed to distribute the computation load across the team in a highly scalable way.

The applications for Unmanned Aerial Vehicles are numerous and cover a range of areas from military applications, scientific projects to commercial activities, but many of these applications require substantial human involvement. This work focuses on the problems and limitations in cooperative Unmanned Aircraft Systems to provide increasing realism for cooperative algorithms. The Consensus Based Bundle Algorithm is extended to remove single agent limits on the task allocation and consensus algorithm. Without this limitation the Consensus Based Grouping Algorithm is proposed that allows the allocation and consensus of multiple agents onto a single task. Solving these problems further increases the usability of cooperative Unmanned Aerial Vehicles groups and reduces the need for human involvement. Additional requirements are taken into consideration including equipment requirements of tasks and creating a specific order for task completion. The Consensus Based Grouping Algorithm provides a conflict free feasible solution to the multi-agent task assignment problem that provides a reasonable assignment without the limitations of previous algorithms. Further to this the new algorithm reduces the amount of communication required for consensus and provides a robust and dynamic data structure for a realistic application. Finally this thesis provides a biologically inspired improvement to the Consensus Based Grouping Algorithm that improves the algorithms performance and solves some of the difficulties it encountered with larger cooperative requirements.

O estudo de sistemas sociais sempre foi visto como fora do escopo da física. No entanto, nos últimos anos, com o desenvolvimento da mecânica estatística e da aprendizagem de máquinas, em conjunto com recentes avanços na neurociência, tornou-se possível a criação de diversos modelos no intuito de estudar quantitativamente grandezas antes consideradas majoritariamente qualitativas. Dentre os problemas considerados está a moralidade, bem como suas consequências para as dinâmicas de opinião. Mais especificamente, considera-se relevante estudar como se dá a mudança de opiniões dentro de uma sociedade, bem como estratégias para convencer uma população a alterar sua direção moral. Utilizando um modelo baseado em agentes, na qual cada agente é representado por um vetor moral e utiliza uma estratégia de aprendizagem ótima para o cenário professor/aluno, estudamos a influência de duas estratégias de convencimento no comportamento macroscópico de nossa sociedade modelo. Tomando como base a aprendizagem sequencial sem a presença de ruído, e o fato de que seleção de exemplos na borda da dúvida gera um decaimento exponencial do erro de generalização em redes neurais artificiais, estudamos o efeito desta técnica como estratégia de convencimento populacional, assim como a comparação de sua eficácia com a estratégia padrão, na qual os exemplos são selecionados uniformemente. / The study of social systems was always seen as out of scope for the physical sciences. However, in the last years, with the rapid development of statistical mechanics and machine learning, along with recent advances in the field of neuroscience, it became possible to create a wide range of models with the objective to investigate quantitatively aspects of sociology that were mainly considered as qualitative features. Within the considered problems lies the issue of morality, as well as it\'s consequences to opinion dynamics. More specifically, it is considered relevant to understand how the opinion change dynamics undergoes inside a society, as well as strategies to convince a population to alter it\'s moral direction. Using an agent based model, in which each agent is represented by a moral vector and has an optimally performing algorithm in the professor/student scenario, we study the influence of two different convincement strategies on the macroscopic behaviour of our model society. In the online learning framework, without any noise, it is known that examples distributed perpendicular to the student achieve a exponential decay in it\'s generalization error. Therefore, we study the effect of this technique as a population convincement strategy, along with it\'s efficiency compared to the standard strategy, in which examples are selected uniformly.

In this study a time based bidding framework is developed which is used for dispatching jobs to manufacturing resources in a virtual shop-floor environment. Agent-based shop-floor control approach is implemented with machine and part agents. The Contract-net communication protocol is utilized as the negotiation scheme between these agents. Single step product reservation (SSPR) technique is adopted throughout the study. Primary objective is determined as meeting the due dates and if the lateness is inevitable, avoiding the parts of high priority from being late. A balanced machine utilization rate is set as the secondary objective. During bid construction step, the SSPR technique is augmented with W(SPT+CR) sequencing rule in order to obtain weighted tardiness results. Bids containing Earliest Finishing Time (EFT) and machine loading values of the corresponding machine are evaluated with considering the priority of the part. An elimination algorithm which discards the highly deviated bids having obvious differences is implemented at the initial stage of the bid evaluation step. A basic algorithm to control the maximum tardiness value is applied, as well. A simulation test bed is developed in order to implement the time concept into the presented bidding framework. The test bed is mainly based on the Computer Integrated Manufacturing Laboratory (CIMLAB) located in Middle East Technical University, Department of Mechanical Engineering. The developed bidding algorithm is tested under several cases. Results revealed that the proposed bidding framework was quite successful in meeting the objectives. The study is concluded with some specific future work, outlined in the light of the results obtained.

Em um ambiente virtual, construído com o uso de tecnologia computacional, encontram-se presentes entidades virtuais inseridas em um espaço tridimensional, que é utilizado para a simulação de processos críticos, como os acidentes radiológicos. A pronta detecção de um acidente radiológico e a determinação da sua possível extensão são fatores essenciais para o planejamento de respostas imediatas e de ações de emergência. A integração das representações georeferenciadas do espaço tridimensional, com modelos baseados em agentes autônomos, com o objetivo de construir ambientes virtuais que tenham a capacidade de simular acidentes radiológicos é a proposta dessa tese. As representações georeferenciadas do espaço tridimensional candidatas são: i)as representações espaciais usadas nos sistemas de informações geográficas (SIG) e ii) a representação adotada pelo Google MapsTM. Com o uso deste ambiente pode-se: quantificar as doses recebidas pelas pessoas; ter uma distribuição espacial das pessoas contaminadas; estimar o número de indivíduos contaminados; estimar o impacto na rede de saúde; estimar impactos ambientais; gerar zonas de exclusão; construir cenários alternativos; treinar pessoal técnico para lidar com acidentes radiológicos. / In a virtual environment, built with the use of computer technology, there are virtual entities, inserted into a virtual three-dimensional space, which is used to simulate critical processes, such as radiological accidents. Early detection of a radiological accident and determining its possible extension are essential for planning an immediate response and emergency actions. The purpose of this thesis is to build virtual environments that have the ability to simulate radiological accidents. These virtual environments are based on the integration of georeferenced representations of the three dimensional space with autonomous agents-based models. The georeferenced representations candidates are: i) the spatial representation used in geographic information systems (GIS); ii) the representation adopted by Google MapsTM. Using these virtual environments, in case of occurrences of radiological accidents, it will be possible to quantify the doses received by people, have a spatial distribution of infected persons; estimate the number of infected individuals; estimate the impact on the health network, estimate environmental impacts, generate exclusion zones, building scenarios alternative; train staff for dealing with these accidents.

Em um ambiente virtual, construído com o uso de tecnologia computacional, encontram-se presentes entidades virtuais inseridas em um espaço tridimensional, que é utilizado para a simulação de processos críticos, como os acidentes radiológicos. A pronta detecção de um acidente radiológico e a determinação da sua possível extensão são fatores essenciais para o planejamento de respostas imediatas e de ações de emergência. A integração das representações georeferenciadas do espaço tridimensional, com modelos baseados em agentes autônomos, com o objetivo de construir ambientes virtuais que tenham a capacidade de simular acidentes radiológicos é a proposta dessa tese. As representações georeferenciadas do espaço tridimensional candidatas são: i)as representações espaciais usadas nos sistemas de informações geográficas (SIG) e ii) a representação adotada pelo Google MapsTM. Com o uso deste ambiente pode-se: quantificar as doses recebidas pelas pessoas; ter uma distribuição espacial das pessoas contaminadas; estimar o número de indivíduos contaminados; estimar o impacto na rede de saúde; estimar impactos ambientais; gerar zonas de exclusão; construir cenários alternativos; treinar pessoal técnico para lidar com acidentes radiológicos. / In a virtual environment, built with the use of computer technology, there are virtual entities, inserted into a virtual three-dimensional space, which is used to simulate critical processes, such as radiological accidents. Early detection of a radiological accident and determining its possible extension are essential for planning an immediate response and emergency actions. The purpose of this thesis is to build virtual environments that have the ability to simulate radiological accidents. These virtual environments are based on the integration of georeferenced representations of the three dimensional space with autonomous agents-based models. The georeferenced representations candidates are: i) the spatial representation used in geographic information systems (GIS); ii) the representation adopted by Google MapsTM. Using these virtual environments, in case of occurrences of radiological accidents, it will be possible to quantify the doses received by people, have a spatial distribution of infected persons; estimate the number of infected individuals; estimate the impact on the health network, estimate environmental impacts, generate exclusion zones, building scenarios alternative; train staff for dealing with these accidents.

O estudo de sistemas sociais sempre foi visto como fora do escopo da física. No entanto, nos últimos anos, com o desenvolvimento da mecânica estatística e da aprendizagem de máquinas, em conjunto com recentes avanços na neurociência, tornou-se possível a criação de diversos modelos no intuito de estudar quantitativamente grandezas antes consideradas majoritariamente qualitativas. Dentre os problemas considerados está a moralidade, bem como suas consequências para as dinâmicas de opinião. Mais especificamente, considera-se relevante estudar como se dá a mudança de opiniões dentro de uma sociedade, bem como estratégias para convencer uma população a alterar sua direção moral. Utilizando um modelo baseado em agentes, na qual cada agente é representado por um vetor moral e utiliza uma estratégia de aprendizagem ótima para o cenário professor/aluno, estudamos a influência de duas estratégias de convencimento no comportamento macroscópico de nossa sociedade modelo. Tomando como base a aprendizagem sequencial sem a presença de ruído, e o fato de que seleção de exemplos na borda da dúvida gera um decaimento exponencial do erro de generalização em redes neurais artificiais, estudamos o efeito desta técnica como estratégia de convencimento populacional, assim como a comparação de sua eficácia com a estratégia padrão, na qual os exemplos são selecionados uniformemente. / The study of social systems was always seen as out of scope for the physical sciences. However, in the last years, with the rapid development of statistical mechanics and machine learning, along with recent advances in the field of neuroscience, it became possible to create a wide range of models with the objective to investigate quantitatively aspects of sociology that were mainly considered as qualitative features. Within the considered problems lies the issue of morality, as well as it\'s consequences to opinion dynamics. More specifically, it is considered relevant to understand how the opinion change dynamics undergoes inside a society, as well as strategies to convince a population to alter it\'s moral direction. Using an agent based model, in which each agent is represented by a moral vector and has an optimally performing algorithm in the professor/student scenario, we study the influence of two different convincement strategies on the macroscopic behaviour of our model society. In the online learning framework, without any noise, it is known that examples distributed perpendicular to the student achieve a exponential decay in it\'s generalization error. Therefore, we study the effect of this technique as a population convincement strategy, along with it\'s efficiency compared to the standard strategy, in which examples are selected uniformly.

Approved for public release, distribution is unlimited / This thesis addresses the need of Naval Aviation Maintenance to streamline and more effectively manage the process of technical consultation aboard deployed aircraft carriers. The current process involves the physical transportation of an appropriate technician to the carrier to perform required maintenance and/or repairs. In light of the technology currently available this process becomes obviously obsolete, overly costly and needlessly time consuming. By implementing wireless technology in combination with advanced software allowing the virtual collaboration of parties widely separated by geographical distance the Navy can establish a "virtual technical presence" onboard aircraft carriers wherever they may be in the world. This thesis will describe how the fusion of wearable computing, augmented reality, intelligent agents coupled with CoABS, and a modern collaborative software application can revolutionize Naval aviation maintenance as we know it. The technology is there - it only remains for the Navy to leverage it and take advantage of the significant returns that it will provide. The implementation of this technology will allow maintainers onboard deployed aircraft carriers to consult in an augmented virtual environment with technical assets on the shore. These shore-based assets will then be able to "walk" deployed personnel through complicated repair procedures in a matter of minutes or hours as opposed to the previous need to wait for days for the technician to arrive. This is a bold and innovative new concept that will allow commands at sea to increase their levels of combat readiness and allow them the ability to respond to ever changing mission needs. Turn around times for the repair of critical parts and assemblies will be reduced and readiness levels elevated. The ultimate goal of any command is mission accomplishment. This system will aid commands in achieving that all important goal. / Lieutenant, United States Navy