Sensory integration model inspired by the superior colliculus for multimodal stimuli localization

Sensory information processing is an important feature of robotic agents that must interact with humans or the environment. For example, numerous attempts have been made to develop robots that have the capability of performing interactive communication. In most cases, individual sensory information is processed and based on this, an output action is performed. In many robotic applications, visual and audio sensors are used to emulate human-like communication. The Superior Colliculus, located in the mid-brain region of the nervous system, carries out similar functionality of audio and visual stimuli integration in both humans and animals. In recent years numerous researchers have attempted integration of sensory information using biological inspiration. A common focus lies in generating a single output state (i.e. a multimodal output) that can localize the source of the audio and visual stimuli. This research addresses the problem and attempts to find an effective solution by investigating various computational and biological mechanisms involved in the generation of multimodal output. A primary goal is to develop a biologically inspired computational architecture using artificial neural networks. The advantage of this approach is that it mimics the behaviour of the Superior Colliculus, which has the potential of enabling more effective human-like communication with robotic agents. The thesis describes the design and development of the architecture, which is constructed from artificial neural networks using radial basis functions. The primary inspiration for the architecture came from emulating the function top and deep layers of the Superior Colliculus, due to their visual and audio stimuli localization mechanisms, respectively. The integration experimental results have successfully demonstrated the key issues, including low-level multimodal stimuli localization, dimensionality reduction of audio and visual input-space without affecting stimuli strength, and stimuli localization with enhancement and depression phenomena. Comparisons have been made between computational and neural network based methods, and unimodal verses multimodal integrated outputs in order to determine the effectiveness of the approach.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

A METHODOLOGY FOR TECHNOLOGY-TUNED DECISION BEHAVIOR ALGORITHMS FOR TACTICS EXPLORATION

In 2016, the USAF found that current development and acquisition methods may be inadequate to achieve air superiority in 2030. The airspace is expected to be highly contested by 2030 due to the Anti-Access/Area Denial strategies being employed by adversaries. Capability gaps must be addressed in order to maintain air superiority. The USAF identified new development and acquisition paradigms as the number one non-material capability development area. The idea of a new development and acquisition paradigm is not new. Such a paradigm shift occurred during the transition from threat-based acquisition during the cold war to capability-based acquisition during the war on terror. Investigation into current US development and acquisition methods found several notional methodologies. Effectiveness-Based Design and Technology Identification, Evaluation, and Selection for Systems-of-Systems have been proposed as notional solutions. Both methodologies seek to evaluate the means – the technologies used to perform a mission – and the ways – the tactics used to complete a mission – of the technology design space. Proper evaluation of the ways would provide critical information to the decision-maker during technology selection. These findings suggest that a new paradigm focused on effectiveness-based acquisition is needed to improve current development and acquisition methods. To evaluate the ways design space, current methods must move away from a fixed or constrained mission model to one that is minimally defined and capable of exploring tactics for each unique technology. The proposed Technology-tuned Decision Behavior Algorithms for Tactics Exploration (Tech-DEBATE) methodology enables the exploration of the ways, or more formally, the mission action design space. The methodology enables further exploration of the technology design space by improving the quantification of mission effectiveness through deep reinforcement learning in a minimally defined mission environment. The data's foundation is based on traceable tactical alternatives that increase the confidence in the measures of effectiveness for each technology-tactic alternative. The methodology enables more informed decisions for technology investment, thereby reducing risks in the development and acquisition of new technologies. The reduction in risk inherently reduces the costs and development time associated with investment in new technologies. The Tech-DEBATE methodology provides a new methodology for technology evaluation through its emphasis on quantifying mission effectiveness in a minimally defined mission to inform technology investment decisions.Ph.D

Arquitecturas Centralizadas de Coordinación. Extrapolación del Fútbol de Robots al Control de Modo de Operaciones de Micro-Redes

[EN] Coordination architectures in multi-agent systems represent an important topic, due to the agents must be organized in order to get a specific objective. In these kinds of systems, robot soccer is shown as an environment with a common frame for research in team coordination. The importance of these kinds of architectures is that the application in other kinds of systems which require coordination. An islanded micro-grid corresponds to a system which can be modeled as multi-agent system, where the distributed energy resources are modeled as agents are coordinated in order to protect the batteries of the energy storage systems, maintaining the common bus regulation. One way to do this throughout coordination strategies, which allow assigning roles and behaviors to the agents, depending on the system conditions. Likewise, the agents must show collaborative behaviors such as making passes in robot soccer, or the equalization of the state of charge for distributed energy storage systems, in order to obtain better results. Multi-agent systems such as robot soccer, that show uncertainties in a hostile environment, require team coordination in order to reach a common goal. One way to achieve this goal is by coordination strategies, which allow role assignment and behavior selection to the players depending on the game conditions. These strategies can present cooperative behaviors among players such as ball passes, in order to obtain better scores against an opponent team. One alternative is the design of hierarchical coordination strategies for an adequate tactic selection, roles assignment and subsequently behavior selection to the players. To this end, one possibility is to use Hierarchical Finite States Machines, due to those allow more flexible and adaptable programming, with a possibility to make changes or modifications. This allows the design of team strategies by an intuitive way according to the control architecture and the rules and specifications of the league where the team plays, in turn performing collaborative behaviors among the players. In this doctoral dissertation are proposed coordination strategies to robot soccer teams, based on tactics, dynamical role assignment and behaviors selection through the use of Finite States Machines, oriented to team architectures with centralized control and global perception. These strategies must allow an intuitive design depending on the team specifications and the rules of the league. These strategies must allow flexibility and adaptability to the necessary changes, such as the number of players, dimensions of the playing field or other changes in the league`s rules. The strategies must be show an adequate response to the failures and allow cooperative behaviors among their players. Lastly, this dissertation presents a structured architecture based on tactics, roles and behaviors for the coordinated operation of islanded microgrids. This grid architecture takes the form of a multi-agent system, and the energy storage and generation units are the team agents. The control strategy is based on the robot soccer strategies presented in this dissertation, which are designed for systems with global perception and centralized control, and in turn determines the changes among operation modes for the distributed energy resources in an islanded microgrid.[ES] Arquitecturas de coordinación en sistemas multi-agente representa un tópico importante, ya que en este tipo de sistemas los agentes deben ser organizados con el fin de obtener un objetivo específico. Dentro de este tipo de sistemas el fútbol de robots se presenta como un entorno que ofrece un marco común para realizar investigaciones en temas relacionados con temas de coordinación de equipo. La importancia de este tipo de arquitecturas radica en su aplicación en otro tipo de ambientes que requieran coordinación. Un sistema que permite este tipo de aplicaciones consiste en una micro-red eléctrica aislada, donde se modelan las fuentes de energía distribuida como agentes que deben ser coordinados con el fin de proteger las baterías de los sistemas de almacenamiento de energía, manteniendo la regulación del bus común. Una forma de conseguir esto es a través de estrategias de coordinación, las cuales permiten asignar roles y comportamientos a los agentes de la forma más adecuada, dependiendo de las condiciones del sistema. Así mismo, también deben presentar comportamientos colaborativos entre los agentes como la realización de pases en el fútbol de robots o la ecualización del estado de carga de las baterías, con el fin de obtener mejores resultados. Una posibilidad para llevar a cabo esta colaboración entre agentes es el diseño de estrategias de coordinación a través de sistemas jerárquicos para la selección de una adecuada táctica. Adicionalmente se debe permitir la asignación de roles y posteriormente la selección de comportamientos de los agentes. Para esto, una alternativa es el uso de Máquinas Jerárquicas de Estado Finito, ya que presentan flexibilidad y adaptabilidad en su programación, siendo fácilmente expandibles a cambios y modificaciones, permitiendo con esto el diseño de estrategias de coordinación de equipo de manera intuitiva acorde con la arquitectura del equipo y los reglamentos de las ligas donde se compita, y a su vez, que permita también el diseño de comportamientos colaborativos entre sus jugadores. En esta tesis doctoral se proponen estrategias de coordinación para fútbol de robots, mediante la selección de tácticas, la asignación dinámica de roles y la selección de comportamientos, usando Máquinas de Estado Finito, enfocándose en el diseño de arquitecturas de equipo que presentan percepción global y control centralizado, y que permitan un diseño intuitivo dependiendo de las especificaciones de los equipos y de la liga en la que se compite. Estas estrategias deben permitir mayor flexibilidad y adaptabilidad frente a posibles cambios, como por ejemplo en el número de jugadores por equipo, en las dimensiones del campo de juego, o en el reglamento de la correspondiente liga. Igualmente deben poseer robustez ante posibles fallos o perturbaciones, permitiendo también comportamientos colaborativos entre sus integrantes. Finalmente se presenta una propuesta para el control del modo de operación de una micro-red aislada, presentando una arquitectura de red como sistema multi-agente, donde las unidades de almacenamiento y generación de energía son los agentes del equipo, y proponiendo una estrategia de control basada en tácticas, roles y comportamientos. Esta arquitectura está basada en las estrategias de fútbol de robots aportadas en esta tesis y las cuales son diseñadas para sistemas con percepción global y control centralizado, que determina los cambios en el modo de operación para las fuentes distribuidas de energía en la micro-red.[CA] Arquitectures de coordinació en sistemes multi-agent representa un tòpic important, perquè en aquest tipus de sistemes els agents deuen organitzar-se per a obtindre un objectiu específic. Dins d'aquest tipus de sistemes, el futbol de robots es presenta com un entorn que ofereix un marc comú per a realitzar investigacions en temes relacionats amb la coordinació d'equips. La importància d'aquest tipus d'arquitectures radica en la seua aplicació en altre tipus d'entorns que requereixin coordinació. Un sistema que permet aquest tipus d'aplicació consisteix en una micro-xarxa elèctrica aïllada, a on es modelitzen les diferents fonts d'energia distribuïdes com agents que deuen ser coordinats per a protegir les bateries dels sistemes de acumulació de energia, mantenint la regulació del bus comú. Una manera d'aconseguir això es mitjançant estratègies de coordinació, que permeten assignar papers i comportaments als agents de la millor forma, en funció de las condicions del sistema. Així mateix, també deuen presentar comportaments col·laboratius entre els agents la realització de passes de futbol de robots o la equalització de la carga de les bateries, amb la finalitat d'obtindre millor resultats. Una possibilitat per a aconseguir aquesta col·laboració entre els agents és el disseny d'estratègies de coordinació mitjançant sistemes jeràrquics per a la selecció d'una tàctica adequada. Addicionalment s'ha de permetre l'assignació de rols i, posteriorment, la selecció de comportaments dels jugadors del equip. Per a açò, una alternativa es l'ús de Màquines Jeràrquiques d'Estat Finit, ja que presenten flexibilitat i adaptabilitat en la seua programació fent que siguin fàcilment expansibles a canvis i modificacions, permetent el disseny d'estratègies de coordinació d'equip de manera intuïtiva relacionant-se amb l'arquitectura de l'equip i el reglament de les lliga en la que estiguin competint, al mateix temps permetent el disseny de comportaments de col·laboració entre els jugadors. En aquesta tesis doctoral es proposen estratègies de coordinació per a futbol de robots, mitjançant la selecció de tàctiques, l'assignació dinàmica de rols y la selecció de comportaments, utilitzant Màquines d'Estat Finit, enfocant-se en el disseny d'arquitectures d'equip que presenten percepció global y control centralitzat, i que puguin permetre un disseny intuïtiu depenent de les especificacions dels equips y de la lliga en la que es competeix. Aquestes estratègies han de permetre major flexibilitat i adaptabilitat davant possibles canvis com podrien ser el nombre de jugadors per equip, les dimensions del camp o el reglament de la corresponent lliga. D'igual manera han de tindre robustesa davant possibles fallades o pertorbacions, permetent també comportaments d'aspecte col·laboratiu entre els seus integrants. En aquesta tesis, finalment es presenta un a proposta per al control del mode d'operació d'una micro-xarxa aïllada, presentant una arquitectura de xarxa com a sistema multi-agent, on les unitats d'emmagatzemament i generació d'energia són els agents del equip, i proposant una estratègia de control basada en tàctiques, rols i comportaments. Aquesta arquitectura està basada en les estratègies de futbol de robots aportades en aquesta tesis i que son dissenyades per a sistemes amb percepció global i control centralitzat, el qual determina els canvis en la forma d'operació per a les fonts distribuïdes d'energia en la micro-xarxa.Guarnizo Marín, JG. (2016). Arquitecturas Centralizadas de Coordinación. Extrapolación del Fútbol de Robots al Control de Modo de Operaciones de Micro-Redes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/68478TESI

Self-adaptive multi-agent systems for aided decision-making : an application to maritime surveillance

L'activité maritime s'est fortement développée ces dernières années et sert de support à de nombreuses activités illicites. Il est devenu nécessaire que les organismes impliqués dans la surveillance maritime disposent de systèmes efficaces pour les aider à identifier ces activités illicites. Les Systèmes de Surveillance Maritime doivent observer de manière efficace un espace maritime large, à identifier des anomalies de comportement des navires évoluant dans l'espace en question, et à déclencher des alertes documentées si ces anomalies amènent à penser que les navires ont un comportement suspect. Nous proposons un modèle générique de système multi-agents, que nous appelons MAS4AT, capable de remplir deux des différents rôles d'un système de surveillance : la représentation numérique des comportements des entités surveillées et des mécanismes d'apprentissage pour une meilleure efficacité. MAS4AT est intégré au système I2C.The maritime activity has widely grow in the last few years and is the witness of several illegal activities. It has become necessary that the organizations involved in the maritime surveillance possess efficient systems to help them in their identification. The maritime surveillance systems must observe a wide maritime area, identify the anomalies in the behaviours of the monitored ships et trigger alerts when these anomalies leads to a suspicious behavior. We propose a generic agent model, called MAS4AT, able to fulfil two main roles of a surveillance system: the numerical representation of the behaviours of the monitored entities and learning mechanisms for a better efficiency. MAS4AT is integrated in the system I2C

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises