ACTORS: A Model of Concurrent Computation in Distributed Systems

A foundational model of concurrency is developed in this thesis. We examine issues in the design of parallel systems and show why the actor model is suitable for exploiting large-scale parallelism. Concurrency in actors is constrained only by the availability of hardware resources and by the logical dependence inherent in the computation. Unlike dataflow and functional programming, however, actors are dynamically reconfigurable and can model shared resources with changing local state. Concurrency is spawned in actors using asynchronous message-passing, pipelining, and the dynamic creation of actors. This thesis deals with some central issues in distributed computing. Specifically, problems of divergence and deadlock are addressed. For example, actors permit dynamic deadlock detection and removal. The problem of divergence is contained because independent transactions can execute concurrently and potentially infinite processes are nevertheless available for interaction.

Reinforcement Learning by Policy Search

One objective of artificial intelligence is to model the behavior of an intelligent agent interacting with its environment. The environment's transformations can be modeled as a Markov chain, whose state is partially observable to the agent and affected by its actions; such processes are known as partially observable Markov decision processes (POMDPs). While the environment's dynamics are assumed to obey certain rules, the agent does not know them and must learn. In this dissertation we focus on the agent's adaptation as captured by the reinforcement learning framework. This means learning a policy---a mapping of observations into actions---based on feedback from the environment. The learning can be viewed as browsing a set of policies while evaluating them by trial through interaction with the environment. The set of policies is constrained by the architecture of the agent's controller. POMDPs require a controller to have a memory. We investigate controllers with memory, including controllers with external memory, finite state controllers and distributed controllers for multi-agent systems. For these various controllers we work out the details of the algorithms which learn by ascending the gradient of expected cumulative reinforcement. Building on statistical learning theory and experiment design theory, a policy evaluation algorithm is developed for the case of experience re-use. We address the question of sufficient experience for uniform convergence of policy evaluation and obtain sample complexity bounds for various estimators. Finally, we demonstrate the performance of the proposed algorithms on several domains, the most complex of which is simulated adaptive packet routing in a telecommunication network.

Teaching an Old Robot New Tricks: Learning Novel Tasks via Interaction with People and Things

As AI has begun to reach out beyond its symbolic, objectivist roots into the embodied, experientialist realm, many projects are exploring different aspects of creating machines which interact with and respond to the world as humans do. Techniques for visual processing, object recognition, emotional response, gesture production and recognition, etc., are necessary components of a complete humanoid robot. However, most projects invariably concentrate on developing a few of these individual components, neglecting the issue of how all of these pieces would eventually fit together. The focus of the work in this dissertation is on creating a framework into which such specific competencies can be embedded, in a way that they can interact with each other and build layers of new functionality. To be of any practical value, such a framework must satisfy the real-world constraints of functioning in real-time with noisy sensors and actuators. The humanoid robot Cog provides an unapologetically adequate platform from which to take on such a challenge. This work makes three contributions to embodied AI. First, it offers a general-purpose architecture for developing behavior-based systems distributed over networks of PC's. Second, it provides a motor-control system that simulates several biological features which impact the development of motor behavior. Third, it develops a framework for a system which enables a robot to learn new behaviors via interacting with itself and the outside world. A few basic functional modules are built into this framework, enough to demonstrate the robot learning some very simple behaviors taught by a human trainer. A primary motivation for this project is the notion that it is practically impossible to build an "intelligent" machine unless it is designed partly to build itself. This work is a proof-of-concept of such an approach to integrating multiple perceptual and motor systems into a complete learning agent.

Learning Commonsense Categorical Knowledge in a Thread Memory System

If we are to understand how we can build machines capable of broad purpose learning and reasoning, we must first aim to build systems that can represent, acquire, and reason about the kinds of commonsense knowledge that we humans have about the world. This endeavor suggests steps such as identifying the kinds of knowledge people commonly have about the world, constructing suitable knowledge representations, and exploring the mechanisms that people use to make judgments about the everyday world. In this work, I contribute to these goals by proposing an architecture for a system that can learn commonsense knowledge about the properties and behavior of objects in the world. The architecture described here augments previous machine learning systems in four ways: (1) it relies on a seven dimensional notion of context, built from information recently given to the system, to learn and reason about objects' properties; (2) it has multiple methods that it can use to reason about objects, so that when one method fails, it can fall back on others; (3) it illustrates the usefulness of reasoning about objects by thinking about their similarity to other, better known objects, and by inferring properties of objects from the categories that they belong to; and (4) it represents an attempt to build an autonomous learner and reasoner, that sets its own goals for learning about the world and deduces new facts by reflecting on its acquired knowledge. This thesis describes this architecture, as well as a first implementation, that can learn from sentences such as ``A blue bird flew to the tree'' and ``The small bird flew to the cage'' that birds can fly. One of the main contributions of this work lies in suggesting a further set of salient ideas about how we can build broader purpose commonsense artificial learners and reasoners.

Interaction and Intelligent Behavior

We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.

Embodied Autonomy in Digital Ecosystems: From Bio-Inspired Agents to Cognitive Systems

This paper proposes to promote autonomy in digital ecosystems so that it provides agents with information to improve the behavior of the digital ecosystem in terms of stability. This work proposes that, in digital ecosystems, autonomous agents can provide fundamental services and information. The final goal is to run the ecosystem, generate novel conditions and let agents exploit them. A set of evaluation measures must be defined as well. We want to provide an outline of some global indicators, such as heterogeneity and diversity, and establish relationships between agent behavior and these global indicators to fully understand interactions between agents, and to understand the dependence and autonomy relations that emerge between the interacting agents. Individual variations, interaction dependencies, and environmental factors are determinants of autonomy that would be considered. The paper concludes with a discussion of situations when autonomy is a milestone

Functional studies of the deubiquitinating enzymes USP19, USP4 and UCH-L1

El marcaje de proteínas con ubiquitina, conocido como ubiquitinación, cumple diferentes funciones que incluyen la regulación de varios procesos celulares, tales como: la degradación de proteínas por medio del proteosoma, la reparación del ADN, la señalización mediada por receptores de membrana, y la endocitosis, entre otras (1). Las moléculas de ubiquitina pueden ser removidas de sus sustratos gracias a la acción de un gran grupo de proteasas, llamadas enzimas deubiquitinizantes (DUBs) (2). Las DUBs son esenciales para la manutención de la homeostasis de la ubiquitina y para la regulación del estado de ubiquitinación de diferentes sustratos. El gran número y la diversidad de DUBs descritas refleja tanto su especificidad como su utilización para regular un amplio espectro de sustratos y vías celulares. Aunque muchas DUBs han sido estudiadas a profundidad, actualmente se desconocen los sustratos y las funciones biológicas de la mayoría de ellas. En este trabajo se investigaron las funciones de las DUBs: USP19, USP4 y UCH-L1. Utilizando varias técnicas de biología molecular y celular se encontró que: i) USP19 es regulada por las ubiquitin ligasas SIAH1 y SIAH2 ii) USP19 es importante para regular HIF-1α, un factor de transcripción clave en la respuesta celular a hipoxia, iii) USP4 interactúa con el proteosoma, iv) La quimera mCherry-UCH-L1 reproduce parcialmente los fenotipos que nuestro grupo ha descrito previamente al usar otros constructos de la misma enzima, y v) UCH-L1 promueve la internalización de la bacteria Yersinia pseudotuberculosis.

Modelo integrador para las rutas de señalización diferencial del receptor ionotrópico de glutamato activado por el N-metil-D-aspartato

El receptor ionotrópico de glutamato activado por N-metil-D-aspartato (iGluR-NMDA) es un complejo macromolecular heteromultimérico constituido por entre 3 y 5 subunidades de tres diferentes tipos, a saber: NR1, NR2A-D y NR3A y B. Se ha demostrado su participación activa en prácticamente todos los procesos fisiológicos, patológicos e intermediarios de efectos farmacológicos que ocurren en las células de tejidos excitables, inclusive se ha reportado su presencia en otros tejidos no excitables. En el sistema nervioso central (SNC) participa en los procesos de aprendizaje, memoria, plasticidad, diferenciación, migración de la célula neural y apoptosis. Además, en los eventos de índole farmacológica se ha demostrado su intervención en excitotoxicidad, drogadicción y alcoholismo. Surge entonces la pregunta de cómo un mismo complejo macromolecular puede participar en tantos y tan diversos procesos. La revisión de literatura en la que se demuestra la interacción del iGluR-NMDA con proteínas de señalización, soporte, adaptadoras, moduladoras, de adhesión celular, de citoesqueleto y enzimas reporta un conjunto de más de 160 moléculas que participan en las cascadas que generan las señales a diferentes niveles de interacción y con diferentes sustratos. En este artículo se presenta un modelo predictivo estructural y funcional que permite distinguir, por lo menos, tres rutas diferenciadas de señalización.

The Integrated Mass Transit Systems Program in Colombia: an Example of Recentralization of the Cities´ Management?

The Integrated Mass Transit Systems are an initiative of the Colombian Government to replicate the experience of Bogota’s Bus Rapid Transit System —Transmilenio— in large urban areas of the country, most of them over municipal perimeters to provide transportation services to areas undergoing a metropolization process. Management of these large scale metropolitan infrastructure projects involves complex setups that present new challenges in the interaction between stakeholders and interests between municipalities, tiers of government and public and private sectors. This article presents a compilation of the management process of these projects from the national context, based on a document review of the regulatory framework, complemented by interviews with key stakeholders at the national level. Research suggests that the implementation of large-scale metropolitan projects requires a management framework orientated to overcome the traditional tensions between centralism and municipal autonomy.

Modelo de gestión del conocimiento para una empresa del sector de insumos químicos para la industria farmacéutica, cosmética y de alimentos: caso Disaromas S.A.

La creación de conocimiento al interior de las organizaciones es visible mediante la dirección adecuada del conocimiento de los individuos, sin embargo, cada individuo debe interactuar de tal manera que forme una red o sistema de conocimiento organizacional que consolide a largo plazo las empresas en el entorno en el que se desenvuelven. Este documento revisa elementos centrales acerca de la gestión de conocimiento visto desde varios autores y perspectivas e identifica puntos clave para diseñar un modelo de gestión de conocimiento para una empresa del sector de insumos químicos para la industria farmacéutica, cosmética y de alimentos de la ciudad de Bogotá.

Select-divide-and-conquer method for large-scale configuration interaction

A select-divide-and-conquer variational method to approximate configuration interaction (CI) is presented. Given an orthonormal set made up of occupied orbitals (Hartree-Fock or similar) and suitable correlation orbitals (natural or localized orbitals), a large N-electron target space S is split into subspaces S0,S1,S2,...,SR. S0, of dimension d0, contains all configurations K with attributes (energy contributions, etc.) above thresholds T0={T0egy, T0etc.}; the CI coefficients in S0 remain always free to vary. S1 accommodates KS with attributes above T1≤T0. An eigenproblem of dimension d0+d1 for S0+S 1 is solved first, after which the last d1 rows and columns are contracted into a single row and column, thus freezing the last d1 CI coefficients hereinafter. The process is repeated with successive Sj(j≥2) chosen so that corresponding CI matrices fit random access memory (RAM). Davidson's eigensolver is used R times. The final energy eigenvalue (lowest or excited one) is always above the corresponding exact eigenvalue in S. Threshold values {Tj;j=0, 1, 2,...,R} regulate accuracy; for large-dimensional S, high accuracy requires S 0+S1 to be solved outside RAM. From there on, however, usually a few Davidson iterations in RAM are needed for each step, so that Hamiltonian matrix-element evaluation becomes rate determining. One μhartree accuracy is achieved for an eigenproblem of order 24 × 106, involving 1.2 × 1012 nonzero matrix elements, and 8.4×109 Slater determinants

Improvement of strategies for the management of fire blight (Erwinia amylovora). Evaluation and optimization of physical and chemical control methods, and use of decision support systems

El foc bacterià és una malaltia que afecta a plantes de la família de la rosàcies, causada pel bacteri Erwinia amylovora. El seu rang d'hostes inclou arbres fruiters, com la perera, la pomera o el codonyer, i plantes ornamentals de gran interès comercial i econòmic. Actualment, la malaltia s'ha dispersat i es troba àmpliament distribuïda en totes les zones de clima temperat del món. A Espanya, on la malaltia no és endèmica, el foc bacterià es va detectar per primer cop al 1995 al nord del país (Euskadi) i posteriorment, han aparegut varis focus en altres localitzacions, que han estat convenientment eradicats. El control del foc bacterià, és molt poc efectiu en plantes afectades per la malaltia, de manera que es basa en mesures encaminades a evitar la dispersió del patogen, i la introducció de la malaltia en regions no endèmiques. En aquest treball, la termoteràpia ha estat avaluada com a mètode d'eradicació d'E. amylovora de material vegetal de propagació asimptomàtic. S'ha demostrat que la termoteràpia és un mètode viable d'eradicar E. amylovora de material de propagació. Gairebé totes les espècies i varietats de rosàcies mantingudes en condicions d'humitat sobrevivien 7 hores a 45 ºC i més de 3 hores a 50 ºC, mentre que més d'1 hora d'exposició a 50 ºC amb calor seca produïa danys en el material vegetal i reduïa la brotació. Tractaments de 60 min a 45 ºC o 30 min a 50 ºC van ser suficients per reduir la població epífita d'E. amylovora a nivells no detectables (5 x 102 ufc g-1 p.f.) en branques de perera. Els derivats dels fosfonats i el benzotiadiazol són efectius en el control del foc bacterià en perera i pomera, tant en condicions de laboratori, com d'hivernacle i camp. Els inductors de defensa de les plantes redueixen els nivells de malaltia fins al 40-60%. Els intervals de temps mínims per aconseguir el millor control de la malaltia van ser 5 dies pel fosetil-Al, i 7 dies per l'etefon i el benzotiadiazol, i les dosis òptimes pel fosetil-Al i el benzotiadiazol van ser 3.72 g HPO32- L-1 i 150 mg i.a. L-1, respectivament. Es millora l'eficàcia del fosetil-Al i del benzotiadiazol en el control del foc bacterià, quan es combinen amb els antibiòtics a la meitat de la dosi d'aquests últims. Tot i que l'estratègia de barrejar productes és més pràctica i fàcil de dur a terme a camp, que l'estratègia de combinar productes, el millor nivell de control de la malaltia s'aconsegueix amb l'estratègia de combinar productes. Es va analitzar a nivell histològic i ultrastructural l'efecte del benzotiadiazol i dels fosfonats en la interacció Erwinia amylovora-perera. Ni el benzotiadiazol, ni el fosetil-Al, ni l'etefon van induir canvis estructurals en els teixits de perera 7 dies després de la seva aplicació. No obstant, després de la inoculació d'E. amylovora es va observar en plantes tractades amb fosetil-Al i etefon una desorganització estructural cel·lular, mentre que en les plantes tractades amb benzotiadiazol aquestes alteracions tissulars van ser retardades. S'han avaluat dos models (Maryblyt, Cougarblight) en un camp a Espanya afectat per la malaltia, per determinar la precisió de les prediccions. Es van utilitzar dos models per elaborar el mapa de risc, el BRS-Powell combinat i el BIS95 modificat. Els resultats van mostrar dos zones amb elevat i baix risc de la malaltia. Maryblyt i Cougarblight són dos models de fàcil ús, tot i que la seva implementació en programes de maneig de la malaltia requereix que siguin avaluats i validats per un període de temps més llarg i en àrees on la malaltia hi estigui present.

Modelling, control and supervision for a class of hybrid systems

The aim of this thesis is to narrow the gap between two different control techniques: the continuous control and the discrete event control techniques DES. This gap can be reduced by the study of Hybrid systems, and by interpreting as Hybrid systems the majority of large-scale systems. In particular, when looking deeply into a process, it is often possible to identify interaction between discrete and continuous signals. Hybrid systems are systems that have both continuous, and discrete signals. Continuous signals are generally supposed continuous and differentiable in time, since discrete signals are neither continuous nor differentiable in time due to their abrupt changes in time. Continuous signals often represent the measure of natural physical magnitudes such as temperature, pressure etc. The discrete signals are normally artificial signals, operated by human artefacts as current, voltage, light etc. Typical processes modelled as Hybrid systems are production systems, chemical process, or continuos production when time and continuous measures interacts with the transport, and stock inventory system. Complex systems as manufacturing lines are hybrid in a global sense. They can be decomposed into several subsystems, and their links. Another motivation for the study of Hybrid systems is the tools developed by other research domains. These tools benefit from the use of temporal logic for the analysis of several properties of Hybrid systems model, and use it to design systems and controllers, which satisfies physical or imposed restrictions. This thesis is focused in particular types of systems with discrete and continuous signals in interaction. That can be modelled hard non-linealities, such as hysteresis, jumps in the state, limit cycles, etc. and their possible non-deterministic future behaviour expressed by an interpretable model description. The Hybrid systems treated in this work are systems with several discrete states, always less than thirty states (it can arrive to NP hard problem), and continuous dynamics evolving with expression: with Ki ¡ Rn constant vectors or matrices for X components vector. In several states the continuous evolution can be several of them Ki = 0. In this formulation, the mathematics can express Time invariant linear system. By the use of this expression for a local part, the combination of several local linear models is possible to represent non-linear systems. And with the interaction with discrete events of the system the model can compose non-linear Hybrid systems. Especially multistage processes with high continuous dynamics are well represented by the proposed methodology. Sate vectors with more than two components, as third order models or higher is well approximated by the proposed approximation. Flexible belt transmission, chemical reactions with initial start-up and mobile robots with important friction are several physical systems, which profits from the benefits of proposed methodology (accuracy). The motivation of this thesis is to obtain a solution that can control and drive the Hybrid systems from the origin or starting point to the goal. How to obtain this solution, and which is the best solution in terms of one cost function subject to the physical restrictions and control actions is analysed. Hybrid systems that have several possible states, different ways to drive the system to the goal and different continuous control signals are problems that motivate this research. The requirements of the system on which we work is: a model that can represent the behaviour of the non-linear systems, and that possibilities the prediction of possible future behaviour for the model, in order to apply an supervisor which decides the optimal and secure action to drive the system toward the goal. Specific problems can be determined by the use of this kind of hybrid models are: - The unity of order. - Control the system along a reachable path. - Control the system in a safe path. - Optimise the cost function. - Modularity of control The proposed model solves the specified problems in the switching models problem, the initial condition calculus and the unity of the order models. Continuous and discrete phenomena are represented in Linear hybrid models, defined with defined eighth-tuple parameters to model different types of hybrid phenomena. Applying a transformation over the state vector : for LTI system we obtain from a two-dimensional SS a single parameter, alpha, which still maintains the dynamical information. Combining this parameter with the system output, a complete description of the system is obtained in a form of a graph in polar representation. Using Tagaki-Sugeno type III is a fuzzy model which include linear time invariant LTI models for each local model, the fuzzyfication of different LTI local model gives as a result a non-linear time invariant model. In our case the output and the alpha measure govern the membership function. Hybrid systems control is a huge task, the processes need to be guided from the Starting point to the desired End point, passing a through of different specific states and points in the trajectory. The system can be structured in different levels of abstraction and the control in three layers for the Hybrid systems from planning the process to produce the actions, these are the planning, the process and control layer. In this case the algorithms will be applied to robotics ¡V a domain where improvements are well accepted ¡V it is expected to find a simple repetitive processes for which the extra effort in complexity can be compensated by some cost reductions. It may be also interesting to implement some control optimisation to processes such as fuel injection, DC-DC converters etc. In order to apply the RW theory of discrete event systems on a Hybrid system, we must abstract the continuous signals and to project the events generated for these signals, to obtain new sets of observable and controllable events. Ramadge & Wonham¡¦s theory along with the TCT software give a Controllable Sublanguage of the legal language generated for a Discrete Event System (DES). Continuous abstraction transforms predicates over continuous variables into controllable or uncontrollable events, and modifies the set of uncontrollable, controllable observable and unobservable events. Continuous signals produce into the system virtual events, when this crosses the bound limits. If this event is deterministic, they can be projected. It is necessary to determine the controllability of this event, in order to assign this to the corresponding set, , controllable, uncontrollable, observable and unobservable set of events. Find optimal trajectories in order to minimise some cost function is the goal of the modelling procedure. Mathematical model for the system allows the user to apply mathematical techniques over this expression. These possibilities are, to minimise a specific cost function, to obtain optimal controllers and to approximate a specific trajectory. The combination of the Dynamic Programming with Bellman Principle of optimality, give us the procedure to solve the minimum time trajectory for Hybrid systems. The problem is greater when there exists interaction between adjacent states. In Hybrid systems the problem is to determine the partial set points to be applied at the local models. Optimal controller can be implemented in each local model in order to assure the minimisation of the local costs. The solution of this problem needs to give us the trajectory to follow the system. Trajectory marked by a set of set points to force the system to passing over them. Several ways are possible to drive the system from the Starting point Xi to the End point Xf. Different ways are interesting in: dynamic sense, minimum states, approximation at set points, etc. These ways need to be safe and viable and RchW. And only one of them must to be applied, normally the best, which minimises the proposed cost function. A Reachable Way, this means the controllable way and safe, will be evaluated in order to obtain which one minimises the cost function. Contribution of this work is a complete framework to work with the majority Hybrid systems, the procedures to model, control and supervise are defined and explained and its use is demonstrated. Also explained is the procedure to model the systems to be analysed for automatic verification. Great improvements were obtained by using this methodology in comparison to using other piecewise linear approximations. It is demonstrated in particular cases this methodology can provide best approximation. The most important contribution of this work, is the Alpha approximation for non-linear systems with high dynamics While this kind of process is not typical, but in this case the Alpha approximation is the best linear approximation to use, and give a compact representation.

Memory-based Embodied Cognition: a computational architecture

At its most fundamental, cognition as displayed by biological agents (such as humans) may be said to consist of the manipulation and utilisation of memory. Recent discussions in the field of cognitive robotics have emphasised the role of embodiment and the necessity of a value or motivation for autonomous behaviour. This work proposes a computational architecture – the Memory-Based Cognitive (MBC) architecture – based upon these considerations for the autonomous development of control of a simple mobile robot. This novel architecture will permit the exploration of theoretical issues in cognitive robotics and animal cognition. Furthermore, the biological inspiration of the architecture is anticipated to result in a mobile robot controller which displays adaptive behaviour in unknown environments.

Improving computer interaction for older people - studying mouse clicks

Interactions using a standard computer mouse can be particularly difficult for novice and older adult users. Tasks that involve positioning the mouse over a target and double-clicking to initiate some action can be a real challenge for many users. Hence, this paper describes a study that investigates the double-click interactions of older and younger adults and presents data that can help inform the development of methods of assistance. Twelve older adults (mean age = 63.9 years) and 12 younger adults (mean age = 20.8 years) performed click and double-click target selections with a computer mouse. Initial results show that older users make approximately twice as many errors as younger users when attempting double-clicks. For both age groups, the largest proportion of errors was due to difficulties with keeping the cursor steady between button presses. Compared with younger adults, older adults experienced more difficulties with performing two button presses within a required time interval. Understanding these interactions better is a step towards improving accessibility, and may provide some suggestions for future directions of research in this area.