Tesis sobre el tema "Architectures cognitives"
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Djerroud, Halim. "Architecture robotique pour la navigation parmi les obstacles amovibles pour un robot mobile". Electronic Thesis or Diss., Paris 8, 2021. http://www.theses.fr/2021PA080050.
In this thesis, we address the autonomous navigation of a mobile robot in a congested indoor environment. This problem is related to navigation among movable obstacles (NAMO). We propose a robotic architecture allowing navigation among: fixed, removable and interactive obstacles. The objective of the robot is to reach a position, while avoiding fixed obstacles, to move removable obstacles if they obstruct the path or to ask interactive obstacles (human, robots, etc.) to give way.In our first contribution, we propose a hierarchical robotic architecture named VICA (VIcarious Cognitive Architecture), whose decisional level is coupled to a cognitive architecture. We are inspired by Alain Berthoz's work on simplexity, which describes how living organisms prepare actions and anticipate reactions. The robotic architecture is composed of a global planner allowing navigation in an unknown environment and a local planner dedicated to obstacle management.The second one implements a global planner whose goal is to bring the robot as close as possible to its goal, using the H* algorithm we have developed.The third one proposes a local planner for obstacle management. The proposed solution consists in using multi-agent simulation in order to anticipate the behavior of obstacles.The implementation of this solution is realized in the VICA architecture developed under ROS (Robot Operating System). In parallel, we have developed an experimental robot to validate our results
Bay, Joo-Hwa. "Cognitive biases in design the case of tropical architecture /". Delft, the Netherlands : Design Knowledge System Research Centre, Faculteit Bouwkunde, Technische Universiteit Delft, 2001. http://catalog.hathitrust.org/api/volumes/oclc/49528245.html.
Bouhali, Florence. "Processing symbols in the ventral visual cortex : functional architecture and anatomical constraints". Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCB080.
The human ventral visual cortex hosts a mosaic of areas specialized in the recognition of different categories of objects. According to a reproducible pattern, some areas respond preferentially to faces, while others are more activated by places and buildings, by tools, or by body parts. Several factors have been proposed as major determinants of the preferred category of a given region, such as visual feature biases (preference for peripheral vs. foveal stimuli, or for high vs. low spatial frequencies), experience (e.g., car expertise) and white-matter connectivity to domain-specific brain networks. In children, learning to read words and other cultural symbols triggers the emergence of dedicated cortical areas, such as the visual word form area (VWFA), within a partially settled ventral pathway. This late ontological development for symbol recognition, free from reading-specific evolutionary constraints, facilitates the investigation of what shapes functional specialization in the ventral pathway. In the current work, we studied in particular the representation of words and musical scores in the ventral visual cortex, using functional magnetic resonance imaging (fMRI), diffusion-weighted imaging and behavioral tasks. First, we show that the location of the VWFA in adults corresponds to a region optimally connected to language regions supporting semantics and phonology, as compared to adjacent ventral cortex regions. Second, we demonstrate that ventral regions supporting orthographic decoding are heterogeneous along a medial-to-lateral axis. Medial regions seem to encode graphemes serially for phonological decoding, under the control of parietal regions. In contrast, lateral regions process words more flexibly for lexical access. These studies reveal a major role of white-matter connectivity in shaping functional specialization for words, with differential connections participating in the functional heterogeneity of the VWFA. Third, we observe that musical literacy has a large impact on lateralization patterns in the ventral stream. A domain general enhancement of leftward lateralization takes place in lateral ventral regions, together with a rightward shift in fusiform regions notably for the processing of faces and houses. These consequences probably reflect both competition between visual categories and transfer across them, and resemble the impact of reading acquisition. Together, our results show that common processes may explain how cultural expertise recycles and modifies the visual cortex
Popescu, Alexandru. "Cognitive Radio Networks : Elements and Architectures". Doctoral thesis, Blekinge Tekniska Högskola, Institutionen för kommunikationssystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00575.
Ratko-Dehnert, Emil. "Distributional constraints on cognitive architecture". Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-159387.
Fawcett, Angela. "A cognitive architecture of dyslexia". Thesis, University of Sheffield, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295122.
Antony, Michael Verne. "Consciousness, content, and cognitive architecture". Thesis, Massachusetts Institute of Technology, 1990. http://hdl.handle.net/1721.1/13729.
Novikova, Jekaterina. "Generic Cognitive Architecture for Real-Time, Embedded Cognitive Systems". Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3889.
Buc, Calderon Cristian. "Temporal dynamics and neural architecture of action selection". Doctoral thesis, Universite Libre de Bruxelles, 2016. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/229408.
Doctorat en Sciences psychologiques et de l'éducation
info:eu-repo/semantics/nonPublished
McHugh, Brendan Thomas. "Architecture as a cognitive teaching device". Thesis, Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/23206.
Thompson, Jill Maria. "Cognitive architecture in euthymic bipolar disorder". Thesis, University of Newcastle Upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.417560.
Harrison, David J. "Connectionism, folk psychology and cognitive architecture". Thesis, University of Sheffield, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322924.
Miri, Hossein. "CernoCAMAL : a probabilistic computational cognitive architecture". Thesis, University of Hull, 2012. http://hydra.hull.ac.uk/resources/hull:6887.
Joshi, Anshul. "WPCA| The Wreath Product Cognitive Architecture". Thesis, The University of Utah, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10242991.
We propose to examine a representation which features combined action and perception signals, i.e., instead of having a purely geometric representation of the perceptual data, we include the motor actions, e.g., aiming a camera at an object, which are also actions that generate the particular shape. This generative perception-action representation uses Leyton’s cognitive representation based on wreath products. The wreath product is a special kind of group which captures information through symmetries on the sensorimotor data. The key insight is the bundling of actuation and perception data together in order to capture the cognitive structure of interactions with the world. This involves developing algorithms and methods: (1) to perform symmetry detection and parsing, (2) to represent and characterize uncertainties in the data and representations, and (3) to provide an overall cognitive architecture for a robot agent. We demonstrate these functions in 2D text classification, as well as on 3D data, on a real robot operating according to a well-defined experimental protocol for benchmarking indoor navigation, along with capabilities for multirobot communication and knowledge sharing. A cognitive architecture called the Wreath Product Cognitive Architecture is developed to support this approach.
Jonas, Eric Michael. "Stochastic architectures for probabilistic computation". Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/87457.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 107-111).
The brain interprets ambiguous sensory information faster and more reliably than modern computers, using neurons that are slower and less reliable than logic gates. But Bayesian inference, which is at the heart of many models for sensory information processing and cognition, as well as many machine intelligence systems, appears computationally challenging, even given modern transistor speeds and energy budgets. The computational principles and structures needed to narrow this gap are unknown. Here I show how to build fast Bayesian computing machines using intentionally stochastic, digital parts, narrowing this efficiency gap by multiple orders of magnitude. By connecting stochastic digital components according to simple mathematical rules, it is possible to rapidly, reliably and accurately solve many Bayesian inference problems using massively parallel, low precision circuits. I show that our circuits can solve problems of depth and motion perception, perceptual learning and causal reasoning via inference over 10,000+ latent variables in real time - a 1,000x speed advantage over commodity microprocessors - by exploiting stochasticity. I will show how this natively stochastic approach follows naturally from the probability algebra, giving rise to easy-to-understand rules for abstraction and composition. I have developed a compiler that automatically generate circuits for a wide variety of problems fixed-structure problems. I then present stochastic computing architectures for models that are viable even when constrained by silicon area and dynamic creation and destruction of random variables. These results thus expose a new role for randomness and Bayesian inference in the engineering and reverse-engineering of computing machines.
by Eric Jonas.
Ph. D.
Zheng, Xijia Ph D. Massachusetts Institute of Technology. "Cognitive optical network architecture in dynamic environments". Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126997.
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 149-154).
Emerging network traffic requires a more agile network management and control system to deal with the dynamic network environments than today's networks use. The bursty and large data transactions introduced by new technological applications can cause both high costs and extreme congestion in networks. The prohibitive cost of massive over-provisioning will manifest as huge congestions during peak demand periods. The network management and control system must be able to sense the traffic changes and reconfigure in a timely manner (in tens of milliseconds instead of minutes or hours) to use network resources efficiently. We propose the use of cognitive techniques for fast and adaptive network management and control of future optical networks. The goal of this work is to provide timely network reconfigurations in response to dynamic traffic environments and prevent congestion from building up.
We make a simplified model of the expected traffic arrival rate changes as a multistate Markov process based on the characteristics of the dynamic, bursty, and high granularity traffic. The traffic is categorized into different network traffic environments by the length of the network coherence time, which is the time that the traffic is unvarying. The tunneled network architecture is adopted due to its supremacy in reducing the control complexity when the traffic volume is at least one wavelength. In the long coherence time regime where traffic changes very slowly, the traffic detection performances of two Bayesian estimators and a stopping-trial (sequential) estimator are examined, based on the transient behaviors of networks. The stopping trial estimator has the fastest response time to the changes of traffic arrival statistics. We propose a wavelength reconfiguration algorithm with continuous assessment where the system reconfigures whenever it deems necessary.
The reconfiguration can involve addition or subtraction of multiple wavelengths. Using the fastest detection and reconfiguration algorithm can reduce queueing delays during traffic surges without over-provisioning and thus can reduce network capital expenditure and prevent wasting resources on erroneous decisions when surges occur. For traffic with moderate coherence time (where traffic changes at a moderate rate) and the short coherence time (where traffic changes quickly), the stopping-trial estimator still responds to the traffic changes with a short detection time. As long as the inter-arrival times of traffic transactions are independent, the algorithm is still optimum. The algorithm provides no prejudice on the exact network traffic distribution, avoiding having to sense and estimate detailed arrival traffic statistics.
To deal with fast-changing traffic, we model the transient convergent behaviors of network traffic drift as a result of traffic transition rate changes and validate the feasibility and utility of the traffic prediction. In a simple example when the network traffic rate changes monotonically in a linear model, the sequential maximum likelihood estimator will capture the traffic trend with a small number of arrivals. The traffic trend prediction can help to provide fast reconfiguration, which is very important for maintaining quality of service during large traffic shifts. We further investigate the design of an efficient rerouting algorithm to maintain users' quality of service when the incremental traffic cannot be accommodated on the primary path. The algorithm includes the fast reconfiguration of wavelengths in the existing lit and spatially routed fibers, and the setting up and lighting of new fibers.
Rerouting is necessary to maintain users' quality of service when the queueing delay on the primary path (determined by shortest path routing) exceeds the requirement. Our algorithm triggers reconfiguration when a queueing delay threshold is crossed on the primary path. The triggering by a threshold on the queueing delay is used due to its simplicity, and it is directly measurable by the exact traffic transaction sizes and the queue size, which reflect both the current network traffic environment and the network configurations. A dynamic rerouting algorithm implemented with a shortest path algorithm is proposed to find the secondary paths for rerouting. We make the conjecture that it is desirable that the alternate paths for rerouting have small numbers of hops and are disjoint with other busy paths when the hops on the path are independent. In addition, the conjecture suggests that a good candidate network topology should have high edge-connectivity.
Wavelength reservation for rerouted traffic does not maximize wavelength utilization. We make the conjecture that traffic with different sizes should be broken up into multi-classes with dedicated partitioned resources and the queueing delay should be normalized by the transmission time for rerouting triggering to realize better network utilization.
by Xijia Zheng.
Ph. D. in Computer Science and Engineering
Ph.D.inComputerScienceandEngineering Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Fox, Nathan Josephe. "Cognitive architecture and the function of human cognition". Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/25027.
Graduate
Foundalis, Harry E. "Phaeaco a cognitive architecture inspired by Bongard's problems /". [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3215222.
Source: Dissertation Abstracts International, Volume: 67-04, Section: B, page: 2251. Adviser: Douglas R. Hofstadter. "Title from dissertation home page (viewed June 20, 2007)."
McGhee, Jeremiah Lane. "Using a Cognitive Architecture in Incremental Sentence Processing". BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3499.
LANZA, Francesco. "Human-Robot Teaming Interaction: a Cognitive Architecture Solution". Doctoral thesis, Università degli Studi di Palermo, 2021. http://hdl.handle.net/10447/479089.
Perdikis, Dionysios. "Functionnal organization of complex behavioral processes". Thesis, Aix-Marseille 2, 2011. http://www.theses.fr/2011AIX22050/document.
Behavioural studies suggest that complex behaviours are multiscale processes, which may be composed of elementary ones (units or primitives). Traditional approaches to cognitive mod-elling generally employ reductionistic (mostly static) representations and computations of simplistic dynamics. The thesis proposes functional architectures to capture the dynamical structure of both functional units and the composite multiscale behaviours. First, a mathe-matical formalism of functional units as low dimensional, structured flows in phase space is introduced (functional modes). Second, additional dynamics (operational signals), which act upon functional modes for complex behaviours to emerge, are classified according to the separation between their characteristic time scale and the one of modes. Then, complexity measures are applied to distinct architectures for a simple composite movement and reveal a trade off between the complexities of functional modes and operational signals, depending on their time scale separation (in support of the control effectiveness of architectures employing non trivial modes). Subsequently, an architecture for serial behaviour (along the example of handwriting) is demonstrated, comprising of functional modes implementing characters, and operational signals much slower (establishing a mode competition and ‘binding’ modes into sequences) or much faster (as meaningful perturbations). All components being coupled, the importance of time scale interactions for behavioural organization is illustrated. Finally, the contributions of modes and signals to the output are recovered, appearing to be possible only through analysis of the output phase flow (i.e., not from trajectories in phase space or time)
Stepanov, Evgueni A. "Implementing Cognitive Grammar On A Cognitive Architecture: A Case Study With Act-r". Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605536/index.pdf.
Kurup, Unmesh. "Design and use of a bimodal cognitive architecture for diagrammatic reasoning and cognitive modeling". Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1198526352.
Dreany, Harry Hayes. "Safety Engineering of Computational Cognitive Architectures within Safety-Critical Systems". Thesis, The George Washington University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10688677.
This paper presents the integration of an intelligent decision support model (IDSM) with a cognitive architecture that controls an autonomous non-deterministic safety-critical system. The IDSM will integrate multi-criteria, decision-making tools via intelligent technologies such as expert systems, fuzzy logic, machine learning, and genetic algorithms.
Cognitive technology is currently simulated within safety-critical systems to highlight variables of interest, interface with intelligent technologies, and provide an environment that improves the system’s cognitive performance. In this study, the IDSM is being applied to an actual safety-critical system, an unmanned surface vehicle (USV) with embedded artificial intelligence (AI) software. The USV’s safety performance is being researched in a simulated and a real-world, maritime based environment. The objective is to build a dynamically changing model to evaluate a cognitive architecture’s ability to ensure safe performance of an intelligent safety-critical system. The IDSM does this by finding a set of key safety performance parameters that can be critiqued via safety measurements, mechanisms, and methodologies. The uniqueness of this research lies in bounding the decision-making associated with the cognitive architecture’s key safety parameters (KSPs). Other real-time applications (RTAs) that would benefit from advancing cognitive science associated with safety are unmanned platforms, transportation technologies, and service robotics. Results will provide cognitive science researchers with a reference for the safety engineering of artificially intelligent safety-critical systems.
MERRYFIELD, JESSICA L. "LET'S PLAY: DESIGNING SPACES FOR COGNITIVE DEVELOPMENT". University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1148070735.
Ong, Chin Chuan. "Analysis of Cognitive Architecture in the Cultural Geography Model". Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/17432.
The Cultural Geography (CG) Model is a multi-agent discrete event simulation developed by TRAC-Monterey. It provides a framework to study the effects of operations in Irregular Warfare, by modeling behavior and interactions of populations. The model is based on social science theories; in particular, agent decision-making algorithms are built on Exploration Learning (EL) and Recognition-Primed Decision (RPD), and trust between entities is modeled to increase realism of interactions. This study analyzed the effects of these components on behavior and scenario outcome. It aimed to identify potential approaches for simplification of the model, and improve traceability and understanding of entity actions. The effect of using EL/RPD with/without trust was tested in basic stand-alone scenarios to assess its impact in isolation on entities perception of civil security. Further testing also investigated the influence on entity behavior in the context of obtaining resources from infrastructure nodes. The findings indicated that choice of decision-making methods did not significantly change scenario outcome, but variance across replications was greater when both EL and RPD were used. Trust was found to delay the rate of change in population stance due to interactions, but did not affect overall outcome if given sufficient time to reach steady state.
DONNART, JEAN-YVES. "Architecture cognitive et proprietes adaptatives d'un animat motivationnellement autonome". Paris 6, 1998. http://www.theses.fr/1998PA066099.
Davis, Robert G. "Cognitive and perceptual factors in lighted architectural environments". Diss., Connect to online resource, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3239430.
Lex, Heiko [Verfasser]. "Granularity of cognitive representations in actions - Advances to the cognitive architecture of actions / Heiko Lex". Bielefeld : Universitätsbibliothek Bielefeld, 2015. http://d-nb.info/1070981370/34.
Hemion, Nikolas [Verfasser]. "Building Blocks for Cognitive Robots: Embodied Simulation and Schemata in a Cognitive Architecture / Nikolas Hemion". Bielefeld : Universitätsbibliothek Bielefeld, 2013. http://d-nb.info/1046174266/34.
Norris, Mary Ann. "The cognitive mapping of musical intention to performance". Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/69274.
Mohsenin, Mahsan (SeyedehMahsan). "The impact of urban geometry on cognitive maps". Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/65743.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 86-87).
This thesis investigates the relationship between urban geometry and cognitive maps. It is focused on the question of how human cognition of the built environment is affected by urban geometry. Building on the foundations of Kevin Lynch's studies of environmental perception (Lynch, 1960) and recent configurational measurement techniques of the built environment, it addresses an important question that Lynch has left unresolved: Why do people have more complete recollections of some parts of the urban environment, and not others? This thesis proposes an analytical measurement framework based on graph theory to compare the results of cognitive maps with objective spatial properties of the corresponding built environment. In order to test our hypothesis, first I measure and define urban geometry based on graph theory in two selected areas with different geometries in Kenmore, Boston and Kendall Sq., Cambridge, MA I will then collect cognitive maps based on specifically designed map drawing surveys. Finally, I examine the relationship between graph results and cognitive maps in order to identify the ways that urban geometry affects human perception. The findings inform urban designers and scholars of the city of how the configuration of the built environment can affect people's memory of a place, thus shaping one's experience of a city. Keywords: configurational patterns, urban geometry, cognitive maps, graph theory.
by Mahsan Mohsenin.
S.M.
Sklivanitis, Georgios. "Software-Defined Architectures for Spectrally Efficient Cognitive Networking in Extreme Environments". Thesis, State University of New York at Buffalo, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10744705.
The objective of this dissertation is the design, development, and experimental evaluation of novel algorithms and reconfigurable radio architectures for spectrally efficient cognitive networking in terrestrial, airborne, and underwater environments. Next-generation wireless communication architectures and networking protocols that maximize spectrum utilization efficiency in congested/contested or low-spectral availability (extreme) communication environments can enable a rich body of applications with unprecedented societal impact. In recent years, underwater wireless networks have attracted significant attention for military and commercial applications including oceanographic data collection, disaster prevention, tactical surveillance, offshore exploration, and pollution monitoring. Unmanned aerial systems that are autonomously networked and fully mobile can assist humans in extreme or difficult-to-reach environments and provide cost-effective wireless connectivity for devices without infrastructure coverage.
Cognitive radio (CR) has emerged as a promising technology to maximize spectral efficiency in dynamically changing communication environments by adaptively reconfiguring radio communication parameters. At the same time, the fast developing technology of software-defined radio (SDR) platforms has enabled hardware realization of cognitive radio algorithms for opportunistic spectrum access. However, existing algorithmic designs and protocols for shared spectrum access do not effectively capture the interdependencies between radio parameters at the physical (PHY), medium-access control (MAC), and network (NET) layers of the network protocol stack. In addition, existing off-the-shelf radio platforms and SDR programmable architectures are far from fulfilling runtime adaptation and reconfiguration across PHY, MAC, and NET layers. Spectrum allocation in cognitive networks with multi-hop communication requirements depends on the location, network traffic load, and interference profile at each network node. As a result, the development and implementation of algorithms and cross-layer reconfigurable radio platforms that can jointly treat space, time, and frequency as a unified resource to be dynamically optimized according to inter- and intra-network interference constraints is of fundamental importance.
In the next chapters, we present novel algorithmic and software/hardware implementation developments toward the deployment of spectrally efficient terrestrial, airborne, and underwater wireless networks. In Chapter 1 we review the state-of-art in commercially available SDR platforms, describe their software and hardware capabilities, and classify them based on their ability to enable rapid prototyping and advance experimental research in wireless networks. Chapter 2 discusses system design and implementation details toward real-time evaluation of a software-radio platform for all-spectrum cognitive channelization in the presence of narrowband or wideband primary stations. All-spectrum channelization is achieved by designing maximum signal-to-interference-plus-noise ratio (SINR) waveforms that span the whole continuum of the device-accessible spectrum, while satisfying peak power and interference temperature (IT) constraints for the secondary and primary users, respectively. In Chapter 3, we introduce the concept of all-spectrum channelization based on max-SINR optimized sparse-binary waveforms, we propose optimal and suboptimal waveform design algorithms, and evaluate their SINR and bit-error-rate (BER) performance in an SDR testbed. Chapter 4 considers the problem of channel estimation with minimal pilot signaling in multi-cell multi-user multi-input multi-output (MIMO) systems with very large antenna arrays at the base station, and proposes a least-squares (LS)-type algorithm that iteratively extracts channel and data estimates from a short record of data measurements. Our algorithmic developments toward spectrally-efficient cognitive networking through joint optimization of channel access code-waveforms and routes in a multi-hop network are described in Chapter 5. Algorithmic designs are software optimized on heterogeneous multi-core general-purpose processor (GPP)-based SDR architectures by leveraging a novel software-radio framework that offers self-optimization and real-time adaptation capabilities at the PHY, MAC, and NET layers of the network protocol stack. Our system design approach is experimentally validated under realistic conditions in a large-scale hybrid ground-air testbed deployment. Chapter 6 reviews the state-of-art in software and hardware platforms for underwater wireless networking and proposes a software-defined acoustic modem prototype that enables (i) cognitive reconfiguration of PHY/MAC parameters, and (ii) cross-technology communication adaptation. The proposed modem design is evaluated in terms of effective communication data rate in both water tank and lake testbed setups. In Chapter 7, we present a novel receiver configuration for code-waveform-based multiple-access underwater communications. The proposed receiver is fully reconfigurable and executes (i) all-spectrum cognitive channelization, and (ii) combined synchronization, channel estimation, and demodulation. Experimental evaluation in terms of SINR and BER show that all-spectrum channelization is a powerful proposition for underwater communications. At the same time, the proposed receiver design can significantly enhance bandwidth utilization. Finally, in Chapter 8, we focus on challenging practical issues that arise in underwater acoustic sensor network setups where co-located multi-antenna sensor deployment is not feasible due to power, computation, and hardware limitations, and design, implement, and evaluate an underwater receiver structure that accounts for multiple carrier frequency and timing offsets in virtual (distributed) MIMO underwater systems.
Gaines, David Alexander. "INVESTIGATIONS INTO THE COGNITIVE ABILITIES OF ALTERNATE LEARNING CLASSIFIER SYSTEM ARCHITECTURES". UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_diss/250.
Raizer, Klaus 1982. "Executive functions for Learning and decision-making in a bio-inspired cognitive architecture = Funções executivas para aprendizado e tomada de decisão em uma arquitetura cognitiva bio-inspirada". [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/261106.
Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação
Made available in DSpace on 2018-08-27T01:31:15Z (GMT). No. of bitstreams: 1 Raizer_Klaus_D.pdf: 4879759 bytes, checksum: 77716297b6419a3ee55bdf97ac67493d (MD5) Previous issue date: 2015
Resumo: O objetivo deste trabalho é o desenvolvimento de funções executivas para uma arquitetura cognitiva bioinspirada baseada em codelets. Um desafio que toda criatura (seja ela artificial ou biológica) enfrenta é definir qual a próxima ação a ser tomada, a cada instante de tempo, em função da percepção de um determinado ambiente. Essa decisão pode ser definida por um algoritmo que sempre repete as mesmas decisões em função de uma determinada situação, ou pode ser uma decisão adaptativa, que utiliza de mecanismos de aprendizagem para assumir decisões distintas, em função das experiências em situações passadas. Neste trabalho, buscou-se a integração dos processos de tomada de decisão deliberativos e mecanismos de aprendizado por reforço em um mesmo framework. Estas funções são conhecidas na literatura de ciências cognitivas como funções executivas. A solução aqui proposta insere-se dentro do contexto de nosso grupo de pesquisa, onde se busca o desenvolvimento de uma arquitetura cognitiva baseada em codelets. Nesta perspectiva, uma das contribuições deste trabalho é desenvolver algoritmos e implementações computacionais dotando a arquitetura cognitiva desenvolvida pelo grupo de funções executivas diversas, que poderão ser utilizadas para implementar soluções complexas com granularidade arbitrária. As funções de tomada de decisão deliberativa foram implementada na forma de uma rede de comportamentos modificada, enquanto que o componente de aprendizado foi desenvolvido na forma de um novo algoritmo (GLAS - Gated-Learning Action Selection) baseado em stimulus gating e inspirado em modelos de neurociência computacional conhecidos da literatura. Este framework foi validado em problemas de robótica móvel e de seleção de ação por aprendizado por reforço. A arquitetura cognitiva sendo desenvolvida, incrementada com as contribuições deste trabalho, tem o potencial de servir de base para futuros trabalhos de pesquisa nas áreas de inteligência artificial, robótica e cognição artificial
Abstract: This work¿s goal is the development of executive functions for a codelet-based bio-inspired cognitive architecture. One of the major challenges every creature faces, being biological or artificial, is to define the next action to be taken, at each time step, as a function of how it perceives its surrounding environment. This decision can be made by a reactive algorithm, which always repeats the same decisions for a given situation, or by an adaptive process, which is able to make use of learning mechanisms in order to make distinct decisions based on past experience. In this work, deliberative decision-making and reinforcement learning mechanisms have been integrated into a single framework. In cognitive science literature, these functions are known as executive functions. The solution proposed here is part of our group¿s central line of research, which is the investigation and development of a codelet-based cognitive architecture. In this context, a central contribution made by this work is the development and implementation of algorithms capable of providing this cognitive architecture with a group of executive functions, which in turn can be used to implement complex solutions with arbitrary granularity. Functions for deliberative decision-making have been implemented in the form of a modified behavior network, while the learning component was developed in the form of a new algorithm called GLAS (Gated-Learning Action Selection), based on stimulus gating and known computational neuroscience models. This framework has been validated with problems in mobile robotics and in action selection by reinforcement learning. The cognitive architecture under development, when incremented by the contributions presented in this work, has the potential to serve as a base for future work and research in the fields of artificial intelligence, robotics and artificial cognition
Doutorado
Engenharia de Computação
Doutor em Engenharia Elétrica
Cahill, Daniel. "Utilising information in architectural design drawings". Thesis, Heriot-Watt University, 2000. http://hdl.handle.net/10399/1143.
Ginhac, Dominique. "Adéquation Algorithme architecture : Aspects logiciels, matériels et cognitifs". Habilitation à diriger des recherches, Université de Bourgogne, 2008. http://tel.archives-ouvertes.fr/tel-00646480.
Bergeron, Vincent. "Cognitive architecture and the brain : beyond domain-specific functional specification". Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/2711.
Le, Bin. "Building a Cognitive Radio: From Architecture Definition to Prototype Implementation". Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/28320.
Ph. D.
Trübutschek, Darinka. "Characterizing the neuro-cognitive architecture of non-conscious working memory". Thesis, Sorbonne université, 2018. http://www.theses.fr/2018SORUS101.
Our lives hinge on our ability to hold information online for immediate use. For over a century, cognitive neuroscientists have regarded such working memory as closely related to consciousness, with both functions sharing similar features and brain mechanisms. Recent work has challenged this view, demonstrating that non-conscious information may affect behavior for several seconds, and suggesting that there exists a genuine non-conscious working memory system. I here combine behavioral and modeling approaches with time-resolved magnetoencephalography and multivariate pattern analysis to put this proposal to the test. In a first study, I rule out alternative explanations for the long-lasting blindsight effect, showing that it results from a genuinely non-conscious process. Crucially, this non-conscious maintenance is not accompanied by persistent delay-period activity, but instead stores information in “activity-silent” brain states via transient changes in synaptic weights. In a second set of experiments, I systematically evaluate key properties of conscious working memory in the context of long-lasting blindsight. While even multiple items and their temporal order may be stored non-consciously, manipulating stored representations is associated with consciousness and sustained neural activity. Together, these results challenge theories that equate the maintenance of information in working memory with conscious activity sustained throughout the delay period, but also contradict the notion of a genuine non-conscious “working” memory. Instead, I propose the existence of activity-silent short-term memory
Kondrakunta, Sravya. "Implementation and Evaluation of Goal Selection in a Cognitive Architecture". Wright State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=wright1503319861179462.
TANEVSKA, ANA. "Towards a Cognitive Architecture for Socially Adaptive Human-Robot Interaction". Doctoral thesis, Università degli studi di Genova, 2020. http://hdl.handle.net/11567/998699.
Tupe, Sameer Vijay. "A Cognitively Inspired Architecture for Wireless Sensor Networks: A Web Service Oriented Middleware for a Traffic Monitoring System". Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/33624.
We describe CoSMo, a Cognitively Inspired Service and Model Architecture for situational awareness and monitoring of vehicular traffic in urban transportation systems using a network of wireless sensors. The system architecture combines (i) a cognitively inspired internal representation for analyzing and answering queries concerning the observed system and (ii) a service oriented architecture that facilitates interaction among individual modules, of the internal representation, the observed system and the user. The cognitively inspired model architecture allows one to effectively respond to deductive as well as inductive queries by combining simulation based dynamic models with traditional relational databases. On the other hand the service oriented design of interaction allows one to build flexible, extensible and scalable systems that can be deployed in practical settings. To illustrate our concepts and the novel features of our architecture, we have recently completed a prototype implementation of CoSMo. The prototype illustrates advantages of our approach over other traditional approaches for designing scalable software for situational awareness in large complex systems. The basic architecture and its prototype implementation are generic and can be applied for monitoring other complex systems. CoSMo's architecture has a number of features that distinguish cognitive systems. This includes: dynamic internal models of the observed system, inductive and deductive learning and reasoning, perception, memory and adaptation.
This thesis describes the service oriented model and the associated prototype implementation. Two important contributions of this thesis include the following:
- The Generic Service Architecture - CoSMo's service architecture is generic and can be applied to many other application domains without much change in underlying infrastructure.
- Integration of emerging web technologies - Use of Web Services, UPnP, UDDI and many other emerging technologies have taken CoSMo beyond a prototype implementation and towards a real production system.
Master of Science
Gursoy, Benay. "The Cognitive Aspects Of Model-making In Architectural Design". Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12611677/index.pdf.
Rast, Alexander Douglas. "Scalable event-driven modelling architectures for neuromimetic hardware". Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/scalable-eventdriven-modelling-architectures-for-neuromimetic-hardware(0c7f08e1-ad35-4cec-94a5-b765e25bab97).html.
Musgrave, John. "Cognitive Malice Representation and Identification". University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1565348664149804.
Lynn, Michael (Michael Benjamin). "Generation and tuning of learned sensorimotor behavior by multiple neural circuit architectures". Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100876.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 25-26).
Organisms have a remarkable ability to respond to complex sensory inputs with intricate, tuned motor patterns. How does the brain organize and tune these motor responses, and are certain circuit architectures, or connectivity patterns, optimally suited for certain sensorimotor applications? This thesis presents progress towards this particular problem in three subprojects. The first section re-analyzes a large data set of single-unit recordings in zebra finch area HVC during singing. While HVC is known to be essential for proper expression of adult vocalization, its circuit architecture is contentious. Evidence is presented against the recently postulated gesture-trajectory extrema hypothesis for the organization of area HVC. Instead, the data suggest that the synaptic chain model of HVC organization is a better fit for the data, where chains of RA-projecting HVC neurons are synaptically connected to walk the bird through each time-step of the song. The second section examines how optimal sensorimotor estimation using a Bayesian inference framework could be implemented in a cerebellar circuit. Two novel behavioral paradigms are developed to assess how rats might tune their motor output to the statistics of the sensory inputs, and whether their behavior might be consistent with the use of a Bayesian inference paradigm. While neither behavior generated stable behavior, evidence indicates that rats may use a spinal circuit to rapidly and dynamically adjust motor output. The third section addresses the formation of habitual behaviors in a cortico-striatal network using rats. Stress and depression are known to significantly alter decision-making abilities, but the neural substrate of this is poorly understood. Towards this goal, rats are trained on a panel of decision-making tasks in a forced-choice T-maze, and it is shown that a chronic stress procedure produces a dramatic shift in behavior in a subset of these tasks but not the rest. This behavioral shift is reversed by optogenetic stimulation of prelimbic input to striatum, pinpointing a circuit element which may control stress-induced behavioral changes. Furthermore, a circuit hypothesis is presented to explain why sensitivity to changing reward values diminishes with overtraining.
by Michael Lynn.
S.M.
Gallagher, Justin (Justin R. ). "An asylum : design specificity for the spectrum of cognitive conditions". Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81654.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 81).
This thesis seeks to re-engage the intimate connection between architecture and the minds of its inhabitants through design that addresses specific cognitive needs. Architecture fundamentally shares a connection with the mind. Through its inhabitants' subjective experience, architecture necessarily interfaces with their cognitive conditions, but to varying extents. This connection was demonstrated most intimately in the architecture and history of the asylum. It was then, when perception was conceived as universal conditions that the built environment participated in the cure of the insane. The result of this attitude was colossal, centralized institutions where those considered insane would be treated. The architectural response to the patients reflected the generalized understanding of the mind at the time--homogenous. Today, the role of architecture has been marginalized as the conception of the mind is strictly chemical and neither environmental nor spatial. As a result, these once colossal institutions are now extinct. Treatment of mental illness is now primarily behavioral therapy and psychoactive drugs, which grow more and more pervasive. Currently, 1 in 4 people have a diagnosable illness. This figure has been used to support the claim for a Mental Illness Crisis in America. And while there maybe be an increase in mental instability, the statistic is more likely a consequence of a new, developing understanding of the mind. That is, through this pursuit to decode our very being into chemical formulas, modern science has revealed a diverse spectrum of cognitive or experiential conditions. The new normal is: there is no normal. The urban condition has already begun to respond to this with the growing network of hospitals, pharmacies, and therapists attending to the mentally ill. However, this thesis projects that soon the mind will be so demystified, that all people will register on a spectrum of cognitive conditions. As a result, architecture will need to respond to not only specific physical requirements such as environment, human body, site, program etc. but to the specific cognitive or experiential needs of the inhabitants. These needs will not longer be recognized as illnesses, but rather as "mindstyles" of the individual. Through the design of three domestic spaces for specific mindstyles--SAD, OCD, and APD--this thesis posits the ability for architecture to behave with the localization and specialization of a pill.
by Justin Gallagher.
S.B.
Glodek, Michael [Verfasser]. "Learning in layered multimodal classifier architectures for cognitive technical systems / Michael Glodek". Ulm : Universität Ulm, 2016. http://d-nb.info/1106329902/34.
Song, Zhiguo. "Systèmes de numérisation hautes performances - Architectures robustes adaptées à la radio cognitive". Phd thesis, Supélec, 2010. http://tel.archives-ouvertes.fr/tel-00589826.