This work is aimed at creating a single view in the field of cognitive processes. Namely it is analysis of providing importance of cognitive processes for the entire field of artificial intelligence. The whole area of cognitive processes is described through the analysis of biological cognitive processes and their subsequent comparison with the processes of artificial intelligence and also the overall analysis of their limitations and their use. The work also contains a brief overview of the architecture of artificial intelligence and philosophical essay focused on the relationship of mind and body. In the end we present a project from IBM workshop, which is very important for their ability to work with natural language and understanding the content of questions asked.

La pérdida de privacidad se está convirtiendo en uno de los mayores problemas en el mundo de la informática. De hecho, la mayoría de los usuarios de Internet (que hoy en día alcanzan la cantidad de 2 billones de usuarios en todo el mundo) están preocupados por su privacidad. Estas preocupaciones también se trasladan a las nuevas ramas de la informática que están emergiendo en los ultimos años. En concreto, en esta tesis nos centramos en la privacidad en los Sistemas Multiagente. En estos sistemas, varios agentes (que pueden ser inteligentes y/o autónomos) interactúan para resolver problemas. Estos agentes suelen encapsular información personal de los usuarios a los que representan (nombres, preferencias, tarjetas de crédito, roles, etc.). Además, estos agentes suelen intercambiar dicha información cuando interactúan entre ellos. Todo esto puede resultar en pérdida de privacidad para los usuarios, y por tanto, provocar que los usuarios se muestren adversos a utilizar estas tecnologías. En esta tesis nos centramos en evitar la colección y el procesado de información personal en Sistemas Multiagente. Para evitar la colección de información, proponemos un modelo para que un agente sea capaz de decidir qué atributos (de la información personal que tiene sobre el usuario al que representa) revelar a otros agentes. Además, proporcionamos una infraestructura de agentes segura, para que una vez que un agente decide revelar un atributo a otro, sólo este último sea capaz de tener acceso a ese atributo, evitando que terceras partes puedan acceder a dicho atributo. Para evitar el procesado de información personal proponemos un modelo de gestión de las identidades de los agentes. Este modelo permite a los agentes la utilización de diferentes identidades para reducir el riesgo del procesado de información. Además, también describimos en esta tesis la implementación de dicho modelo en una plataforma de agentes. / Such Aparicio, JM. (2011). ENHANCING PRIVACY IN MULTI-AGENT SYSTEMS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/13023 / Palancia

Actualmente, los sistemas informáticos complejos se describen en términos de entidades que actúan como proveedores y consumidores. Estas entidades ofrecen su funcionalidad a través de servicios e interactúan entre ellas para ofrecer o pedir estos servicios. La integración de Sistemas Multi-Agente Abiertos y de Sistemas Orientados a Servicios es adecuada para implementar este tipo de sistemas. En los SMA abiertos, los agentes entran y salen del sistema, interactúan con los demás de una manera flexible, y se consideran como entidades reactivas y proactivas, capaces de razonar acerca de lo que sucede en su entorno y llevar a cabo acciones locales sobre la base de sus observaciones para alcanzar sus metas. El área de la computación orientada a servicios proporciona los bloques de construcción básicos para aplicaciones empresariales complejas que son los servicios. Los servicios son independientes de la plataforma y pueden ser descubiertos y compuestos de manera dinámica. Estas características hacen que los servicios sean adecuados para hacer frente a la elevada tasa de cambios en las demandas de las empresas. Sin embargo, la complejidad de los sistemas informáticos, los cambios en las condiciones del entorno y el conocimiento parcial de los agentes sobre el sistema requieren que los agentes cuenten con mecanismos que les faciliten tareas como el descubrimiento de servicios, la auto-organización de sus relaciones estructurales conforme se producen cambios en la demanda de servicios, y la promoción y mantenimiento de un comportamiento cooperativo entre los agentes para garantizar el buen desarrollo de la actividad de descubrimiento de servicios en el sistema. La principal aportación de esta tesis doctoral es la propuesta de un marco para Sistemas Multi-Agente Abiertos Orientados a Servicios. Este marco integra agentes que se encuentran en una red sin ningún tipo de estructura predefinida, y agentes que además de estar en esa red forman parte de grupos dinámicos más comp / Del Val Noguera, E. (2013). Semantic Service management for service-oriented MAS [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/27556 / Palancia

Organizations have become the backbone of the society. Humans live around all kinds of organizations, such as neighborhood communities, businesses, schools, unions, political, sports, and religious organizations, etc. These organizations have a set of members, each playing a specific role, which determines their duties and functionalities within the organization. One of these functionalities is to offer a range of services to members of the organization and external people. These members must follow a set of norms to ensure the proper functioning of the organization and should pursue the global goals of the organization. A feature that is repeated in organizations is that they are not static but dynamic, resulting in changes in both its structure and the way in which they behave. In an organization, any of its elements is prone to change due to situations that occur in the organization itself or its environment. Researchers in the field of social sciences and organizations have studied such situations, the reasons why they appear and solutions and actions to be taken to ensure that this situation does not damage the organization or to take advantage of the situation. These situations are known as ‘Forces that drive organizational change’. Human organizations are the main source of inspiration for the Multi-Agent Systems (MAS) based on organizations. These systems are computational abstractions that are populated by agents instead of people, but take into account organizational elements such as roles, services, goals, norms, etc. However, the proposals that have been presented up to now to define this type of MAS are focused mostly on static systems, without changes in its structure. Moreover, in the few proposals that take into account organizational changes, they just state that changes occur, but without specifying the reason for change. Thus, the concept of ‘forces that drive organizational change’ (and their features) is not considered. Therefore, the objective of this PhD thesis is to translate the knowledge of the forces that drive organizational change available in human organizations to MASbased organizations. These forces will be formally expressed with the factors that help to detect them. The solutions to be taken when a force is detected will also be presented. To correctly perform this task, a formalization for virtual organizations is designed, named Virtual Organization Formalization (VOF). Moreover, the Artifacts for Organizational Mechanisms are proposed, which are a tool to help in the representation of organizational knowledge and in the modeling of the environment of the organization. This tool is based on the Agents & Artifacts (A&A) framework. / Esparcia García, S. (2015). Integrating driving forces into the development of Adaptive Virtual Organizations [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48538 / TESIS

[pt] Transparência é um critério de qualidade crítico para sociedades democráticas modernas. Como o software permeia a sociedade, a transparência se tornou uma preocupação para softwares operando em domínios públicos, sejam eles eGovernment, eCommerce ou softwares sociais. Dessa forma, a transparência de software está se tornando um critério de qualidade que demanda mais atenção dos desenvolvedores de software. Requisitos de transparência em um sistema de software estão relacionados a requisitos não-funcionais, como disponibilidade, usabilidade, informatividade, entendimento e auditabilidade. Entretanto, requisitos de transparência são especialmente difíceis de serem validados devido à natureza subjetiva dos conceitos envolvidos. Essa tese propõe o desenvolvimento intencional de software transparente dirigido por requisitos de transparência. Os requisitos de transparência são elicitados com o apoio de um catálogo de padrões de requisitos, relativamente validados pelos interessados através do uso de argumentação e representados em modelos intencionais. Modelos intencionais são fundamentais para a transparência de software, uma vez que associam aos requisitos as metas e os critérios de qualidade esperados pelos interessados e que justificam as decisões tomadas. Um sistema exemplo foi implementado como um sistema multi-agentes intencional, ou seja, com agentes colaborativos que implementam o modelo Belief-Desire-Intention e que são capazes de raciocinar sobre metas e critérios de qualidade. Essa tese discute as questões importantes para o sucesso da nossa abordagem de desenvolvimento de software transparente, como: (i) rastreabilidade requisitos-código e código-requisitos; (ii) o uso de lógica nebulosa para desenvolver uma máquina de raciocínio para agentes intencionais; (iii) a aplicação de argumentação para a validação relativa de requisitos de transparência através da obtenção de um consenso entre os interessados; e (iv) pré-rastreabilidade colaborativa para modelos intencionais baseada nas interações sociais. Nossas idéias foram validadas através de estudos de caso em diferentes domínios, tal como computação ubíqua e aplicações Web. / [en] Transparency is a critical quality criterion to modern democratic societies. As software permeates society, transparency has become a concern to public domain software, as eGovernment, eCommerce or social software. Therefore, software transparency is becoming a quality criterion that demands more attention from software developers. In particular, transparency requirements of a software system are related to non-functional requirements, e.g. availability, usability, informativeness, understandability and auditability. However, transparency requirements are particularly difficult to validate due to the subjective nature of the involved concepts. This thesis proposes a transparency-requirements-driven intentional development of transparent software. Transparency requirements are elicited with the support of a requirements patterns catalog, relatively validated by the stakeholders through argumentation and represented on intentional models. Intentional models are fundamental to software transparency, as they associate goals and quality criteria expected by the stakeholders with the software requirements. The goals and quality criteria also justify the decisions made during software development. A system was implemented as an intentional multi-agents system, i.e., a system with collaborative agents that implement the Belief-Desire- Intention model and that are capable of reasoning about goals and quality criteria. This thesis discusses important questions to the success of our approach to the development of transparent software, such as: (i) forward and backward traceability; (ii) a fuzzy-logic based reasoning engine for intentional agents; (iii) the application of an argumentation framework to relatively validate transparency requirements through stakeholders’ multi-party agreement; and (iv) collaborative pre-traceability for intentional models based on social interactions. Our ideas were validated through case studies from different domains, such as ubiquitous computing and Web applications.

This Ph.D. thesis deals with trust modelling for distributed systems especially to multi-context trust modelling for multi-agent distributed systems. There exists many trust and reputation models but most of them do not dealt with the multi-context property of trust or reputation. Therefore, the main focus of this thesis is on analysis of multi-context trust based models and provides main assumptions for new fully multi-contextual trust model on the bases of them. The main part of this thesis is in providing new formal multi-context trust model which are able to build, update and maintain trust value for different aspects (contexts) of the single entity in the multi-agent system. In our proposal, trust value can be built on the bases of direct interactions or on the bases on recommendations and reputation. Moreover we assume that some context of one agent is not fully independent and on the bases of trust about one of them we are able to infer trust to another's. Main contribution of this new model is increasing the efficiency in agent decision making in terms of optimal partner selection for interactions. Proposed model was verified by implementing prototype of multi-agent system when trust was used for agents' decision making and acting.

Bien que le domaine des systèmes multi-agents ait été largement étudié, les interactions entre agents entraînent des pertes de privacité. En effet, la résolution de problèmes distribués, étant fréquemment combinatoires, impose un échange intensif d’informations entre les agents jusqu’à l’obtention d’un accord. Le problème est que les approches existantes ne considèrent généralement pas la confidentialité des données et se concentrent surtout sur la satisfaction des contraintes des agents pour évaluer les solutions. Les travaux présentés dans cette thèse visent donc à prendre en compte de façon principielle la problématique de la privacité dans le raisonnement distribué. Nous montrons que les travaux existants dans le domaine permettent toutefois aux agents de préserver implicitement un certain degré de privacité. Nous proposons une approche basée sur la théorie de l’utilité, un cadre formel bien défini en Intelligence Artificielle, permettant une approche objective et quantitative des intérêts et comportements raisonnables des agents. Plus précisément, le modèle que nous avons développé inclut non seulement les paramètres habituels mais également l’information sur la privacité des agents quantifiée en termes d’utilité. Nous montrons aussi que ces problèmes doivent être envisagés comme des problèmes de planification où les agents choisissent des actions maximisant leur utilité. Des algorithmes actuels peuvent être décrits comme des plans utilisables comme modèle générique par des planificateurs intelligents. Les expérimentations réalisées ont permis de valider l’approche et d’évaluer la qualité des solutions obtenues tout en montrant que leur efficacité peut être accrue à l’aide de traitements de privacité. / Although the field of multi-agent systems has been largely studied, interactions between agents imply privacy loss. Indeed, solving distributed problems, being frequently combinatorial, implies an extensive exchange of information between agents until an agreement is found. The problem is that existing approaches do not generally consider privacy and focus only on the satisfaction of agents’ constraints to evaluate solution. The works presented in this thesis therefore aim at considering systematically the issue of privacy in distributed reasoning. We show that existing works in the field still let agents preserve implicitly some degree of privacy. We propose an approach based on utility theory, a formal setting well defined in Artificial Intelligence, allowing an objective and quantitative approach to the interests and reasonable behaviours of agents. More precisely, the model we have developed includes non only the usual parameters but also information on agents privacy quantified in term of utility. We also show that these problems must be considered as planning problems where agents choose actions maximizing their utility. Common algorithms can be described as plans usable as generic models by intelligent planners. Conducted experiments let us validate the approach and evaluate the quality of obtained solution, while showing that their efficiency can be improved thanks to privacy considerations.

Nous visons à garantir la résolution d’un DisCSP en présence d’un ou plusieurs agents défaillants. Les méthodes traitant la tolérance aux fautes au sein des SMAs visent la continuité du fonctionnement du système. Mais, aucune de ces méthodes n’est appliquée pour résoudre un DisCSP. La défaillance d’un agent au cours de la résolution d’un DisCSP engendre la perte d’une partie du DisCSP global, d’où l’obtention d’un résultat erroné. Donc pour obtenir les résultats attendus, il faut garantir la résolution du CSP local de l’agent défaillant. Nous proposons de répliquer les CSPs locaux des agents défaillants au sein des agents non défaillants. Cette réplication permet la résolution du CSP local de l’agent défaillant par un autre agent. Cette résolution est effectuée en fusionnant les réplicats de CSPs des agents défaillants avec les CSPs des autres agents. Cette fusion permet la conservation de la modélisation initiale du DisCSP. L’algorithme de distribution des réplicats proposé garantit que les CSPs des agents défaillants ne soient pas répliqués au sein du même agent. De cette façon, le problème conserve son aspect distribué. / We aim to ensure a DisCSP resolution in presence of failed agents. Methods handling fault tolerance in MASs aim to ensure the continuity of the system operation. But, none of these methods are applied to solve a DisCSP. The failure of an agent generates the loss of a part of the DisCSP providing wrong results. Therefore, to obtain expected results, it is necessary to ensure the resolution of the failed agent local CSP.We propose to replicate the local CSPs of the failed agents within active agents. This replication allows local CSP resolution of the failed agent by another agent. The resolution is done by merging the replicates of failed agents CSPs with the CSPs of other agents. This technique conserve the initial DisCSP modeling. The proposed replicates distribution algorithm ensures that the CSPs of failed agents are not replicated within the same agent. In this way, the problem keeps its distributed aspect.

<div>Distributed estimation algorithms have received considerable attention lately, owing to the advancements in computing, communication and battery technologies. They offer increased scalability, robustness and efficiency. In applications such as formation flight, where any discrepancies between sensor estimates has severe consequences, it becomes crucial to require consensus of estimates amongst all sensors. The Kalman Consensus Filter (KCF) is a seminal work in the field of distributed consensus-based estimation, which accomplishes this. </div><div><br></div><div>However, the KCF algorithm is mathematically sub-optimal, and does not account for the cross-correlation between the estimates of sensors. Other popular algorithms, such as the Information weighted Consensus Filter (ICF) rely on ad-hoc definitions and approximations, rendering them sub-optimal as well. Another major drawback of KCF is that it utilizes unweighted consensus, i.e., each sensor assigns equal weightage to the estimates of its neighbors. This fact has been shown to cause severely degraded performance of KCF when some sensors cannot observe the target, and can even cause the algorithm to be unstable.</div><div><br></div><div>In this work, we develop a novel algorithm, which we call Optimal Kalman Consensus Filter for Weighted Directed Graphs (OKCF-WDG), which addresses both of these limitations of existing algorithms. OKCF-WDG integrates the KCF formulation with that of matrix-weighted consensus. The algorithm achieves consensus on a weighted digraph, enabling a directed flow of information within the network. This aspect of the algorithm is shown to offer significant performance improvements over KCF, as the information may be directed from well-performing sensors to other sensors which have high estimation error due to environmental factors or sensor limitations. We validate the algorithm through simulations and compare it to existing algorithms. It is shown that the proposed algorithm outperforms existing algorithms by a considerable margin, especially in the case where some sensors are naive (i.e., cannot observe the target).</div>

In the last few years, as processing the data became a part of everyday life in different areas of human activity, the automated machine learning systems that are designed to help with the process of data mining, are on the rise. Various metalearning techniques, including recommendation of the right method to use, or the sequence of steps to take, and to find its optimum hyperparameters configuration, are integrated into these systems to help the researchers with the machine learning tasks. In this thesis, we proposed metalearning algorithms and techniques for hyperparameters optimization, narrowing the intervals of hyperparameters, and recommendations of a machine learning method for a never before seen dataset. We designed two AutoML machine learning systems, where these metalearning techniques are implemented. The extensive set of experiments was proposed to evaluate these algorithms, and the results are presented.