This thesis describes the architecture of an adaptive goal-oriented AI system that can be used for Real-Time Strategy games. The system is at the end tested against a single opponent on three different maps with different sizes to test the ability of the AI opposed to the 'standard' Finite State Machines and the likes in Real-Time Strategy games. The system consists of a task handler agent that manages all the active and halted tasks. A task is either low-level; used for ordering units, or high-level that can form advanced strategies. The General forms plans that are most beneficial at the moment. For creating effective units against the opponent a priority system is used; where the unit priorities are calculated dynamically. / Den här uppsatsen beskriver en adaptiv målorienterad AI-arkitektur som kan tillämpas på "Real-Time Strategy" spel. Systemet testat mot en annan AI som använder mer traditionella "Finite State Machines" in sin arkitekture. Testet utförs på tre olika banor som är olika stora. Systemet består utav en "Uppgiftshanterare" som har hand om alla aktiva och inaktiva uppgifter. En uppgift kan antingen vara utav låg-nivå, som används för att skicka kommandon till enheterna, eller utav hög-nivå för att göra mer avancerade strategier. Generalen planerar och skapar uppgifter som är mest fördelaktig för tillfället. För att skapa enheter som är effektiva mot fiendens enheter används ett prioritetssystem, där enhetens prioritet kalkyleras ut dynamiskt under spelets gång.

An architecture for actionbased planning and cooperation between multiple AI-agents based on the GOAP-architecture was developed together with a system to be used in advanced AI-courses at Linköping unversity. The architecture was implemented in this system to show the possibilities of our work.

The field of artificial intelligence has gained much knowledge through the implementation of decision-making systems in video games. One of these systems was the Goal Oriented Action Planning system (GOAP) which directs the behavior of an AI-agent through multiple digital artifacts categorized as goals, actions, and plans. The aim of the thesis is to aid in the understanding and creation of GOAP driven AI-agents in a video game setting to promote research on this topic. The research question of this thesis was about finding out how the GOAP architecture compares to other video game decision-making systems. The theoretical framework introduces the concept of the illusion of intelligence in video games and presents a discussion focused on the different components which make up a GOAP system and other components that support it. Additionally, the theoretical framework explains the need for a comparison between different decision-making systems and explains the social impact of game AI research. The methods section introduces the criteria for the comparison between GOAP and other decision-making systems and presents a comparison process that was driven by a literature review. A GOAP system was designed for this thesis using the unified modeling language and concept maps. It was then implemented using C# code in a free-of-charge game engine called Unity. We present the pseudocode for the implementation of the GOAP system and show that this framework is a modular, customizable, and reusable system that enables AI-agents to create plans from a varied set of actions. Finally, the paper suggests further research within game decision-making AI and emphasizes the importance of game AI research for communities of game developers, hobbyists, and others who could benefit from game AI in their projects.

Introduction: Primary care in Flanders is undergoing reform. Researchers are looking at ways to understand the context in order to be able to implement person-centred and goal-oriented care approaches such as reablement. Aim: The aim was to illuminate the lived experiences of older people with chronic conditions and what it means to receive paid care at home. Method: Using an interpretative phenomenological analysis approach, this study aimed to understand the lived experience of someone living at home receiving paid care. Results: Six in depth interviews were analysed generating nine themes and related subthemes. Conclusions: The study illuminated the experiences of six people who received care at home and generated themes around autonomy, adaptability, respect, identity, flexibility, self determination, power, acceptance, and control that reflected the literature and concepts around person-centred and goal-oriented care as well as the importance of the role of occupational therapy. Significance: In the Flemish context, this was the first study looking at the experiences of people living at home with paid care and the chances and barriers to reablement and occupational therapy in the community setting.

Organizations use Business Intelligence (BI) systems to monitor how well they are meeting their goals and objectives. Yet, very often BI systems do not include clear models of the organization’s goals or of how to measure whether they are satisfied or not. Several researchers now attempt to integrate goal models into BI systems, but there are still major challenges related to how to get access to the BI data to populate the part of the goal model (often indicators) used to assess goal satisfaction. This thesis explores a new approach to integrate BI systems with goal models. In particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open source graphical editor for the User Requirements Notation (URN), which includes the Use Case Map notation for scenarios and processes and the Goal-oriented Requirement Language for business objectives. URN was recently extended with the concept of Key Performance Indicator (KPI) to enable performance assessment and monitoring of business processes. In jUCMNav, KPIs are currently calculated or modified manually. The new integration proposed in this thesis maps these KPIs to report elements that are generated automatically by Cognos based on the model defined in jUCMNav at runtime, with minimum effort. We are using IBM Cognos Mashup Service, which includes web services that enable the retrieval of report elements at the most granular level. This transformation provides managers and analysts with useful goal-oriented and process-oriented monitoring views fed by just-in-time BI information. This new solution also automates retrieving data from Cognos servers, which helps reducing the high costs usually caused by the amount of manual work required otherwise. The novel approach presented in this thesis avoids manual report generation and minimizes any contract with respect to the location of manually created reports, hence leading to better usability and performance. The approach and its tool support are illustrated with an ongoing example, validated with a case study, and verified through testing.

Organizations use Business Intelligence (BI) systems to monitor how well they are meeting their goals and objectives. Yet, very often BI systems do not include clear models of the organization’s goals or of how to measure whether they are satisfied or not. Several researchers now attempt to integrate goal models into BI systems, but there are still major challenges related to how to get access to the BI data to populate the part of the goal model (often indicators) used to assess goal satisfaction. This thesis explores a new approach to integrate BI systems with goal models. In particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open source graphical editor for the User Requirements Notation (URN), which includes the Use Case Map notation for scenarios and processes and the Goal-oriented Requirement Language for business objectives. URN was recently extended with the concept of Key Performance Indicator (KPI) to enable performance assessment and monitoring of business processes. In jUCMNav, KPIs are currently calculated or modified manually. The new integration proposed in this thesis maps these KPIs to report elements that are generated automatically by Cognos based on the model defined in jUCMNav at runtime, with minimum effort. We are using IBM Cognos Mashup Service, which includes web services that enable the retrieval of report elements at the most granular level. This transformation provides managers and analysts with useful goal-oriented and process-oriented monitoring views fed by just-in-time BI information. This new solution also automates retrieving data from Cognos servers, which helps reducing the high costs usually caused by the amount of manual work required otherwise. The novel approach presented in this thesis avoids manual report generation and minimizes any contract with respect to the location of manually created reports, hence leading to better usability and performance. The approach and its tool support are illustrated with an ongoing example, validated with a case study, and verified through testing.

Organizations use Business Intelligence (BI) systems to monitor how well they are meeting their goals and objectives. Yet, very often BI systems do not include clear models of the organization’s goals or of how to measure whether they are satisfied or not. Several researchers now attempt to integrate goal models into BI systems, but there are still major challenges related to how to get access to the BI data to populate the part of the goal model (often indicators) used to assess goal satisfaction. This thesis explores a new approach to integrate BI systems with goal models. In particular, it explores the integration of IBM Cognos Business Intelligence, a leading BI tool, with an Eclipse-based goal modeling tool named jUCMNav. jUCMNav is an open source graphical editor for the User Requirements Notation (URN), which includes the Use Case Map notation for scenarios and processes and the Goal-oriented Requirement Language for business objectives. URN was recently extended with the concept of Key Performance Indicator (KPI) to enable performance assessment and monitoring of business processes. In jUCMNav, KPIs are currently calculated or modified manually. The new integration proposed in this thesis maps these KPIs to report elements that are generated automatically by Cognos based on the model defined in jUCMNav at runtime, with minimum effort. We are using IBM Cognos Mashup Service, which includes web services that enable the retrieval of report elements at the most granular level. This transformation provides managers and analysts with useful goal-oriented and process-oriented monitoring views fed by just-in-time BI information. This new solution also automates retrieving data from Cognos servers, which helps reducing the high costs usually caused by the amount of manual work required otherwise. The novel approach presented in this thesis avoids manual report generation and minimizes any contract with respect to the location of manually created reports, hence leading to better usability and performance. The approach and its tool support are illustrated with an ongoing example, validated with a case study, and verified through testing.

In order to research the limited English proficiency of First Year National Intermediate Certificate students at the Further Education and Training College of Ekurhuleni West, the researcher investigated various motivation variables, namely: * socio-psychological factors * learner factors * parental involvement and * contextual factors related to the influence of the school and classroom A review of literature and empirical research methods were used to this effect. The literature review revealed that instrumental and integrative motivation, self-determination and goal orientedness, parental support and school and classroom context factors contributed to the development of ESL proficiency. A motivation questionnaire and an English proficiency test were administered to the participants. The results indicated no significant relationship between the learner's level of ESL proficiency and motivation variables. These findings form the basis for recommending specific guidelines for possible directions for future research. / Linguistics / M.A. (Specialisation in Applied Linguistics)

Miss Kathy is a documentary film that tells the story of Kathy Griffin-Grinan, a lead recovery coach for prostitution and human trafficking with the Harris County Sheriff’s Office. Her non-profit organization —We’ve Been There, Done That – works in conjunction with law-enforcement to offer the survivors of prostitution a chance at rehabilitation. With endless enthusiasm, she mentors survivors as they struggle to escape a destructive lifestyle. This film also explores the relationship between human trafficking and prostitution, while addressing issues of victimization and exploitation.

Dans un contexte d'adaptabilité ciblée, l'erreur commise sur une quantité d'intérêt peut être représentée grâce aux erreurs globales des problèmes direct et adjoint. Cette représentation de l'erreur est majorée par la somme des indicateurs d'erreurs élémentaires. Ces derniers sont alors utilisés pour produire des raffinements de maillage optimaux. Dans ces travaux, nous proposons de représenter l’erreur du problème adjoint via un opérateur alternatif. L’avantage principal de notre approche est que lorsque l'on choisit correctement l'opérateur alternatif, la majoration correspondante de l'erreur à la quantité d'intérêt devient plus précise, pour autant l'adaptabilité issue de l'utilisation de ces nouveaux indicateurs s'en trouve améliorée. Ces représentations peuvent être employées pour concevoir des algorithmes adaptatifs en espace (h), en ordre d’approximation (p) ou les deux (hp), basés sur la norme d’énergie ou bien ciblés sur une quantité d'intérêt. Bien que la méthode puisse être appliquée à une large gamme de problèmes, nous nous concentrons tout d’abord sur des problèmes unidimensionnels (1D), comme le problème d’Helmholtz et le problème de convection-diffusion stationnaire à convection dominante. Les résultats numériques en 1D montrent que, pour les problèmes de propagation d'ondes, les avantages de notre méthode sont notoires lorsque l'on considère l'opérateur de Laplace pour la représentation de l'erreur. Plus précisément, les majorations issues de la nouvelle représentation sont plus précises que celles provenant de la méthode classique et ce si l'on considère l'énergie globale ou bien une quantité d'intérêt particulière. Le phénomène est d’autant plus notable lorsque l'erreur de dispersion (pollution) est significative. Le problème 1D de convection-diffusion stationnaire à convection dominante avec des conditions limites de Dirichlet homogènes présente une couche limite qui produit une perte de stabilité numérique. La nouvelle représentation d'erreur délivre des majorations plus précises. Lorsqu’appliquée à une p-adaptabilité ciblée, la représentation d'erreur alternative permet une capture plus efficace la couche limite, malgré les oscillations numériques parasites existantes. Devant ces résultats encourageants, nous nous penchons sur l'équation d'Helmholtz à deux et trois dimensions (2D et 3D). Nous montrons, au travers de multiples simulations numériques, que les majorations fournies par les représentations d'erreur alternatives sont plus précises que celle de la représentation classique. Lorsque l'on utilise les indicateurs d'erreur alternatifs, un processus naïf de p-adaptabilité ciblée converge, tandis que dans les mêmes conditions, la méthode classique échoue et requiert l'utilisation d'un opérateur de projection ou d'autre techniques pour récupérer la convergence. Dans ce travail, nous fournissons également des directives pour déterminer les opérateurs qui fournissent des représentations d’erreur induisant de majorations précises. Des résultats similaires sont aussi établis tant pour un problème 2D de convection-diffusion stationnaire à convection dominante que pour des problèmes 2D ayant des coefficients de matériaux discontinus. Nous considérons un problème de diagraphie ultra-sonique en cours de forage pour illustrer l'applicabilité de la méthode proposée. / In Goal-Oriented Adaptivity (GOA), the error in a Quantity of Interest (QoI) is represented using global error functions of the direct and adjoint problems. This error representation is subsequently bounded above by element-wise error indicators that are used to drive optimal refinements. In this work, we propose to replace, in the error representation, the adjoint problem by an alternative operator. The main advantage of the proposed approach is that, when judiciously selecting such alternative operator, the corresponding upper bound of the error representation becomes sharper, leading to a more efficient GOA. These representations can be employed to design novel h, p, and hp energy-norm and goal-oriented adaptive algorithms. While the method can be applied to a variety of problems, in this Dissertation we first focus on one-dimensional (1D) problems, including Helmholtz and steady state convection-dominated diffusion problems. Numerical results in 1D show that for the Helmholtz problem, it is advantageous to select the Laplace operator for the alternative error representation. Specifically, the upper bounds of the new error representation are sharper than the classical ones used in both energy-norm and goal-oriented adaptive methods, especially when the dispersion (pollution) error is significant. The 1D steady state convection-dominated diffusion problem with homogeneous Dirichlet boundary conditions exhibits a boundary layer that produces a loss of numerical stability. The new error representation based on the Laplace operator delivers sharper error upper bounds. When applied to a p-GOA, the alternative error representation captures earlier the boundary layer, despite the existing spurious numerical oscillations. We then focus on the two- and three-dimensional (2D and 3D) Helmholtz equation. We show via extensive numerical experimentation that the upper bounds provided by the alternative error representations are sharper than the classical ones. When using the alternative error indicators, a naive p-adaptive process converges, whereas under the same conditions, the classical method fails and requires the use of the so-called Projection Based Interpolation (PBI) operator or some other technique to regain convergence. We also provide guidelines for finding operators delivering sharp error representation upper bounds. / En un contexto de adaptatividad orientada a un objetivo, el error en una cantidad de interés está representado a través de los errores globales de los problemas directo y adjunto. Esta representación del error se acota superiormente por una suma de indicadores de error de cada elemento. Estos se utilizan para producir refinamientos óptimos. En este trabajo, proponemos representar el error del problema adjunto utilizando un operador alternativo. La principal ventaja de nuestro enfoque es que cuando se elige correctamente dicho operador alternativo, la correspondiente cota superior se vuelve más cercana al error en la cantidad de interés, lo que permite una adaptatividad más eficiente. Estas representaciones pueden ser utilizadas para diseñar algoritmos adaptativos en h, p o hp, basados en la norma de la energía o para aproximar una cantidad de interés específica. Aunque el método propuesto se puede aplicar a una amplia gama de problemas, en esta tesis doctoral nos centramos primero en problemas unidimensionales (1D), tales como el problema de Helmholtz y el problema estacionario de convección-difusión con convección dominante. Los resultados numéricos en 1D muestran que, para los problemas de propagación de ondas, las ventajas de este método son notorias cuando se considera el operador de Laplace para la representación del error. Específicamente, las cotas superiores derivadas de la nueva representación son más cercanas a la cantidad de interés que las del método convencional. Esto es cierto tanto para la norma de la energía global como para una cantidad de interés particular, especialmente cuando el error de dispersión es significativo. El problema estacionario 1D de convección-difusión con convección dominante y con condiciones de Dirichlet homogéneas tiene una capa límite que produce una pérdida de estabilidad numérica. La nueva representación del error proporciona cotas superiores más cercanas a la cantidad de interés. Cuando se aplica a un algoritmo adaptativo en p orientado a un objetivo, la representación alternativa del error captura antes la capa límite, a pesar de las existentes oscilaciones numéricas no físicas. En esta tesis doctoral, también nos centramos en la ecuación de Helmholtz en dos y tres dimensiones (2D y 3D). Mostramos a través de múltiples experimentos numéricos que las cotas superiores proporcionadas por las representaciones alternativas del error son más cercanas a la cantidad de interés que cuando uno considera la representación clásica. Al utilizar los indicadores alternativos del error, un algoritmo adaptativo en p sencillo converge, mientras que en las mismas condiciones, el método convencional falla y requiere el uso de operadores de proyección o de otras técnicas para recuperar la convergencia. En este trabajo, también determinamos operadores que proporcionan representaciones del error que inducen cotas superiores más ajustadas. Establecemos resultados similares tanto para el problema estacionario de convección-difusión con convección dominante en 2D como para problemas 2D con materiales discontinuos. Finalmente, se considera un problema sónico en pozos petrolíferos para ilustrar la aplicabilidad del método propuesto.