Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

Face detection in C#

Actualmente la detección del rostro humano es un tema difícil debido a varios parámetros implicados. Llega a ser de interés cada vez mayor en diversos campos de aplicaciones como en la identificación personal, la interface hombre-máquina, etc. La mayoría de las imágenes del rostro contienen un fondo que se debe eliminar/discriminar para poder así detectar el rostro humano. Así, este proyecto trata el diseño y la implementación de un sistema de detección facial humana, como el primer paso en el proceso, dejando abierto el camino, para en un posible futuro, ampliar este proyecto al siguiente paso, que sería, el Reconocimiento Facial, tema que no trataremos aquí. En la literatura científica, uno de los trabajos más importantes de detección de rostros en tiempo real es el algoritmo de Viola and Jones, que ha sido tras su uso y con las librerías de Open CV, el algoritmo elegido para el desarrollo de este proyecto. A continuación explicaré un breve resumen sobre el funcionamiento de mi aplicación. Mi aplicación puede capturar video en tiempo real y reconocer el rostro que la Webcam captura frente al resto de objetos que se pueden visualizar a través de ella. Para saber que el rostro es detectado, éste es recuadrado en su totalidad y seguido si este mueve. A su vez, si el usuario lo desea, puede guardar la imagen que la cámara esté mostrando, pudiéndola almacenar en cualquier directorio del PC. Además, incluí la opción de poder detectar el rostro humano sobre una imagen fija, cualquiera que tengamos guardada en nuestro PC, siendo mostradas el número de caras detectadas y pudiendo visualizarlas sucesivamente cuantas veces queramos. Para todo ello como bien he mencionado antes, el algoritmo usado para la detección facial es el de Viola and Jones. Este algoritmo se basa en el escaneo de toda la superficie de la imagen en busca del rostro humano, para ello, primero la imagen se transforma a escala de grises y luego se analiza dicha imagen, mostrando como resultado el rostro encuadrado. ABSTRACT Currently the detection of human face is a difficult issue due to various parameters involved. Becomes of increasing interest in various fields of applications such as personal identification, the man-machine interface, etc. Most of the face images contain a fund to be removed / discriminate in order to detect the human face. Thus, this project is the design and implementation of a human face detection system, as the first step in the process, leaving the way open for a possible future, extend this project to the next step would be, Facial Recognition , a topic not covered here. In the literature, one of the most important face detection in real time is the algorithm of Viola and Jones, who has been after use with Open CV libraries, the algorithm chosen for the development of this project. I will explain a brief summary of the performance of my application. My application can capture video in real time and recognize the face that the Webcam Capture compared to other objects that can be viewed through it. To know that the face is detected, it is fully boxed and followed if this move. In turn, if the user may want to save the image that the camera is showing, could store in any directory on your PC. I also included the option to detect the human face on a still image, whatever we have stored in your PC, being shown the number of faces detected and can view them on more times. For all as well I mentioned before, the algorithm used for face detection is that of Viola and Jones. This algorithm is based on scanning the entire surface of the image for the human face, for this, first the image is converted to gray-scale and then analyzed the image, showing results in the face framed.

Knowledge Discovery in Spectral Data by Means of Complex Networks

In the last decade, complex networks have widely been applied to the study of many natural and man-made systems, and to the extraction of meaningful information from the interaction structures created by genes and proteins. Nevertheless, less attention has been devoted to metabonomics, due to the lack of a natural network representation of spectral data. Here we define a technique for reconstructing networks from spectral data sets, where nodes represent spectral bins, and pairs of them are connected when their intensities follow a pattern associated with a disease. The structural analysis of the resulting network can then be used to feed standard data-mining algorithms, for instance for the classification of new (unlabeled) subjects. Furthermore, we show how the structure of the network is resilient to the presence of external additive noise, and how it can be used to extract relevant knowledge about the development of the disease.

El Entorno Aumentado: Imperativo informacional para una ecología digital de lo arquitectónico

Esta tesis se suma a los intentos teóricos de clarificar la impronta del dominio digital en lo arquitectónico. Propone una cartografía crítica para reconstruir el proceso de tal convergencia considerando aquellos acontecimientos reveladores que lo han pautado. La integración de la extensión digital propia las tecnologías de la información y la comunicación en el contexto tradicional arquitectónico ha supuesto el advenimiento de un ecosistema artificial complejo. A esta realidad o proceso concurrente se la denomina el Entorno Aumentado. La línea principal de investigación explora el desarrollo de la interacción hombre-máquina, en sendas trayectorias sincrónicas convergentes. El análisis se aborda por tanto desde la consideración de esa naturaleza dual, atendiendo simultáneamente a la humanización del dominio digital o cómo la computación se adapta a la condición natural de ser humano, y a la digitalización del ser humano o cómo éste asume el imperativo digital. El análisis resulta vertebrado desde la condición panóptica del punto de observación del acontecimiento: la cuarta pared, entendida como pantalla y punto de inflexión que estructura la convergencia de los entornos físico y digital. La reflexión acometida sobre la construcción del Entorno Aumentado procura la verificación de la tesis, que es central en esta investigación: la multiplicación dimensional del lugar físico mediante su extensión con un campo informacional procedente del dominio digital, y sus efectos en la construcción de la nueva ecología digital propia del Entorno Aumentado. Esta circunstancia se produce tras la eclosión de la Revolución Digital en la segunda mitad del siglo XX, el consecuente incremento de la interacción entre los entornos digital y físico, y el alcance de un nivel superior de comunicación en los procesos arquitectónicos. Los síntomas del Entorno Aumentado se hacen notar en nuestra contemporaneidad; en ese sentido, la tesis alcanza un diagnóstico del cambio. La fractura y obsolescencia del límite espacio-temporal establecido por las dicotomías históricas privado-público, casa-ciudad, trabajo-ocio,…etc., o la vigencia del proyecto procedimental son algunas de sus consecuencias en el modo de abordar la disciplina arquitectónica. Abstract This dissertation aims to complete the theoretical attempts to clarify the digital domain imprint on the architectural realm. It constructs a critical cartography to reconstruct the process of such convergence, considering those principal events who have scheduled it. The integration of TIC’s digital extension through the traditional architectural context has meant the advent of an artificial complex ecosystem. This reality or concurrent process is called The Augmented Environment. The key research attempt explores man-machine interaction process in both synchronous converging trajectories. The analysis therefore addresses from the consideration of this dual nature, focusing simultaneously in humanizing digital domain process or how the computer fits the natural condition of human beings, and in digitalizing human beings or how it affords the digital imperative. The analysis is structured from the panoptic condition of the event scope: the fourth wall as screen that structures the convergence of physical and digital environments. The examination of The Augmented Environment’s assembly pretends the verification of the central point of this research: the dimensional multiplication of physical space by extending informational fields from the digital domain, and its effects on the construction of the Augmented Environment new digital ecology. This circumstance occurs after the arrival of the Digital Revolution in the second half of the twentieth century, with the consequent increase in the interaction between digital and physical environments, and the reach of a higher level of communication in architectural processes. The Augmented Environment signs are alive nowadays; in that sense, the thesis reaches a diagnostic of the changes. The fracture and obsolescence of the time-space limit established by historic dichotomies as private-public, home-city, working-leisure...etc., or the validity of the procedural design are some of its consequences on the architectural discipline.

A documentation generator for (C)LP systems

We describe lpdoc, a tool which generates documentation manuals automatically from one or more logic program source files, written in Ciao, ISO-Prolog, and other (C)LP languages. It is particularly useful for documenting library modules, for which it automatically generates a rich description of the module interface. However, it can also be used quite successfully to document full applications. A fundamental advantage of using lpdoc is that it helps maintaining a true correspondence between the program and its documentation, and also identifying precisely to what versión of the program a given printed manual corresponds. The quality of the documentation generated can be greatly enhanced by including within the program text assertions (declarations with types, modes, etc. ...) for the predicates in the program, and machine-readable comments. One of the main novelties of lpdoc is that these assertions and comments are written using the Ciao system asseriion language, which is also the language of communication between the compiler and the user and between the components of the compiler. This allows a significant synergy among specification, debugging, documentation, optimization, etc. A simple compatibility library allows conventional (C)LP systems to ignore these assertions and comments and treat normally programs documented in this way. The documentation can be generated interactively from emacs or from the command line, in many formats including texinfo, dvi, ps, pdf, info, ascii, html/css, Unix nroff/man, Windows help, etc., and can include bibliographic citations and images, lpdoc can also genérate "man" pages (Unix man page format), nicely formatted plain ASCII "readme" files, installation scripts useful when the manuals are included in software distributions, brief descriptions in html/css or info formats suitable for inclusión in on-line Índices of manuals, and even complete WWW and info sites containing on-line catalogs of documents and software distributions. The lpdoc manual, all other Ciao system manuals, and parts of this paper are generated by lpdoc.

A documentation generator for logic programming systems

We describe lpdoc, a tool which generates documentation manuals automatically from one or more logic program source files, written in ISO-Prolog, Ciao, and other (C)LP languages. It is particularly useful for documenting library modules, for which it automatically generates a rich description of the module interface. However, it can also be used quite successfully to document full applications. The documentation can be generated in many formats including t e x i n f o, dvi, ps, pdf, inf o, html/css, Unix nrof f/man, Windows help, etc., and can include bibliographic citations and images, lpdoc can also genérate "man" pages (Unix man page format), nicely formatted plain ascii "readme" files, installation scripts useful when the manuals are included in software distributions, brief descriptions in html/css or inf o formats suitable for inclusión in on-line Índices of manuals, and even complete WWW and inf o sites containing on-line catalogs of documents and software distributions. A fundamental advantage of using lpdoc is that it helps maintaining a true correspondence between the program and its documentation, and also identifying precisely to what versión of the program a given printed manual corresponds. The quality of the documentation generated can be greatly enhanced by including within the program text assertions (declarations with types, modes, etc. ...) for the predicates in the program, and machine-readable comments. These assertions and comments are written using the Ciao system assertion language. A simple compatibility library allows conventional (C)LP systems to ignore these assertions and comments and treat normally programs documented in this way. The lpdoc manual, all other Ciao system manuals, and most of this paper, are generated by lpdoc.

Contributions to the contextualization of human-machine spoken interaction systems

The design and development of spoken interaction systems has been a thoroughly studied research scope for the last decades. The aim is to obtain systems with the ability to interact with human agents with a high degree of naturalness and efficiency, allowing them to carry out the actions they desire using speech, as it is the most natural means of communication between humans. To achieve that degree of naturalness, it is not enough to endow systems with the ability to accurately understand the user’s utterances and to properly react to them, even considering the information provided by the user in his or her previous interactions. The system has also to be aware of the evolution of the conditions under which the interaction takes place, in order to act the most coherent way as possible at each moment. Consequently, one of the most important features of the system is that it has to be context-aware. This context awareness of the system can be reflected in the modification of the behaviour of the system taking into account the current situation of the interaction. For instance, the system should decide which action it has to carry out, or the way to perform it, depending on the user that requests it, on the way that the user addresses the system, on the characteristics of the environment in which the interaction takes place, and so on. In other words, the system has to adapt its behaviour to these evolving elements of the interaction. Moreover that adaptation has to be carried out, if possible, in such a way that the user: i) does not perceive that the system has to make any additional effort, or to devote interaction time to perform tasks other than carrying out the requested actions, and ii) does not have to provide the system with any additional information to carry out the adaptation, which could imply a lesser efficiency of the interaction, since users should devote several interactions only to allow the system to become adapted. In the state-of-the-art spoken dialogue systems, researchers have proposed several disparate strategies to adapt the elements of the system to different conditions of the interaction (such as the acoustic characteristics of a specific user’s speech, the actions previously requested, and so on). Nevertheless, to our knowledge there is not any consensus on the procedures to carry out these adaptation. The approaches are to an extent unrelated from one another, in the sense that each one considers different pieces of information, and the treatment of that information is different taking into account the adaptation carried out. In this regard, the main contributions of this Thesis are the following ones: Definition of a contextualization framework. We propose a unified approach that can cover any strategy to adapt the behaviour of a dialogue system to the conditions of the interaction (i.e. the context). In our theoretical definition of the contextualization framework we consider the system’s context as all the sources of variability present at any time of the interaction, either those ones related to the environment in which the interaction takes place, or to the human agent that addresses the system at each moment. Our proposal relies on three aspects that any contextualization approach should fulfill: plasticity (i.e. the system has to be able to modify its behaviour in the most proactive way taking into account the conditions under which the interaction takes place), adaptivity (i.e. the system has also to be able to consider the most appropriate sources of information at each moment, both environmental and user- and dialogue-dependent, to effectively adapt to the conditions aforementioned), and transparency (i.e. the system has to carry out the contextualizaton-related tasks in such a way that the user neither perceives them nor has to do any effort in providing the system with any information that it needs to perform that contextualization). Additionally, we could include a generality aspect to our proposed framework: the main features of the framework should be easy to adopt in any dialogue system, regardless of the solution proposed to manage the dialogue. Once we define the theoretical basis of our contextualization framework, we propose two cases of study on its application in a spoken dialogue system. We focus on two aspects of the interaction: the contextualization of the speech recognition models, and the incorporation of user-specific information into the dialogue flow. One of the modules of a dialogue system that is more prone to be contextualized is the speech recognition system. This module makes use of several models to emit a recognition hypothesis from the user’s speech signal. Generally speaking, a recognition system considers two types of models: an acoustic one (that models each of the phonemes that the recognition system has to consider) and a linguistic one (that models the sequences of words that make sense for the system). In this work we contextualize the language model of the recognition system in such a way that it takes into account the information provided by the user in both his or her current utterance and in the previous ones. These utterances convey information useful to help the system in the recognition of the next utterance. The contextualization approach that we propose consists of a dynamic adaptation of the language model that is used by the recognition system. We carry out this adaptation by means of a linear interpolation between several models. Instead of training the best interpolation weights, we make them dependent on the conditions of the dialogue. In our approach, the system itself will obtain these weights as a function of the reliability of the different elements of information available, such as the semantic concepts extracted from the user’s utterance, the actions that he or she wants to carry out, the information provided in the previous interactions, and so on. One of the aspects more frequently addressed in Human-Computer Interaction research is the inclusion of user specific characteristics into the information structures managed by the system. The idea is to take into account the features that make each user different from the others in order to offer to each particular user different services (or the same service, but in a different way). We could consider this approach as a user-dependent contextualization of the system. In our work we propose the definition of a user model that contains all the information of each user that could be potentially useful to the system at a given moment of the interaction. In particular we will analyze the actions that each user carries out throughout his or her interaction. The objective is to determine which of these actions become the preferences of that user. We represent the specific information of each user as a feature vector. Each of the characteristics that the system will take into account has a confidence score associated. With these elements, we propose a probabilistic definition of a user preference, as the action whose likelihood of being addressed by the user is greater than the one for the rest of actions. To include the user dependent information into the dialogue flow, we modify the information structures on which the dialogue manager relies to retrieve information that could be needed to solve the actions addressed by the user. Usage preferences become another source of contextual information that will be considered by the system towards a more efficient interaction (since the new information source will help to decrease the need of the system to ask users for additional information, thus reducing the number of turns needed to carry out a specific action). To test the benefits of the contextualization framework that we propose, we carry out an evaluation of the two strategies aforementioned. We gather several performance metrics, both objective and subjective, that allow us to compare the improvements of a contextualized system against the baseline one. We will also gather the user’s opinions as regards their perceptions on the behaviour of the system, and its degree of adaptation to the specific features of each interaction. Resumen El diseño y el desarrollo de sistemas de interacción hablada ha sido objeto de profundo estudio durante las pasadas décadas. El propósito es la consecución de sistemas con la capacidad de interactuar con agentes humanos con un alto grado de eficiencia y naturalidad. De esta manera, los usuarios pueden desempeñar las tareas que deseen empleando la voz, que es el medio de comunicación más natural para los humanos. A fin de alcanzar el grado de naturalidad deseado, no basta con dotar a los sistemas de la abilidad de comprender las intervenciones de los usuarios y reaccionar a ellas de manera apropiada (teniendo en consideración, incluso, la información proporcionada en previas interacciones). Adicionalmente, el sistema ha de ser consciente de las condiciones bajo las cuales transcurre la interacción, así como de la evolución de las mismas, de tal manera que pueda actuar de la manera más coherente en cada instante de la interacción. En consecuencia, una de las características primordiales del sistema es que debe ser sensible al contexto. Esta capacidad del sistema de conocer y emplear el contexto de la interacción puede verse reflejada en la modificación de su comportamiento debida a las características actuales de la interacción. Por ejemplo, el sistema debería decidir cuál es la acción más apropiada, o la mejor manera de llevarla a término, dependiendo del usuario que la solicita, del modo en el que lo hace, etcétera. En otras palabras, el sistema ha de adaptar su comportamiento a tales elementos mutables (o dinámicos) de la interacción. Dos características adicionales son requeridas a dicha adaptación: i) el usuario no ha de percibir que el sistema dedica recursos (temporales o computacionales) a realizar tareas distintas a las que aquél le solicita, y ii) el usuario no ha de dedicar esfuerzo alguno a proporcionar al sistema información adicional para llevar a cabo la interacción. Esto último implicaría una menor eficiencia de la interacción, puesto que los usuarios deberían dedicar parte de la misma a proporcionar información al sistema para su adaptación, sin ningún beneficio inmediato. En los sistemas de diálogo hablado propuestos en la literatura, se han propuesto diferentes estrategias para llevar a cabo la adaptación de los elementos del sistema a las diferentes condiciones de la interacción (tales como las características acústicas del habla de un usuario particular, o a las acciones a las que se ha referido con anterioridad). Sin embargo, no existe una estrategia fija para proceder a dicha adaptación, sino que las mismas no suelen guardar una relación entre sí. En este sentido, cada una de ellas tiene en cuenta distintas fuentes de información, la cual es tratada de manera diferente en función de las características de la adaptación buscada. Teniendo en cuenta lo anterior, las contribuciones principales de esta Tesis son las siguientes: Definición de un marco de contextualización. Proponemos un criterio unificador que pueda cubrir cualquier estrategia de adaptación del comportamiento de un sistema de diálogo a las condiciones de la interacción (esto es, el contexto de la misma). En nuestra definición teórica del marco de contextualización consideramos el contexto del sistema como todas aquellas fuentes de variabilidad presentes en cualquier instante de la interacción, ya estén relacionadas con el entorno en el que tiene lugar la interacción, ya dependan del agente humano que se dirige al sistema en cada momento. Nuestra propuesta se basa en tres aspectos que cualquier estrategia de contextualización debería cumplir: plasticidad (es decir, el sistema ha de ser capaz de modificar su comportamiento de la manera más proactiva posible, teniendo en cuenta las condiciones en las que tiene lugar la interacción), adaptabilidad (esto es, el sistema ha de ser capaz de considerar la información oportuna en cada instante, ya dependa del entorno o del usuario, de tal manera que adecúe su comportamiento de manera eficaz a las condiciones mencionadas), y transparencia (que implica que el sistema ha de desarrollar las tareas relacionadas con la contextualización de tal manera que el usuario no perciba la manera en que dichas tareas se llevan a cabo, ni tampoco deba proporcionar al sistema con información adicional alguna). De manera adicional, incluiremos en el marco propuesto el aspecto de la generalidad: las características del marco de contextualización han de ser portables a cualquier sistema de diálogo, con independencia de la solución propuesta en los mismos para gestionar el diálogo. Una vez hemos definido las características de alto nivel de nuestro marco de contextualización, proponemos dos estrategias de aplicación del mismo a un sistema de diálogo hablado. Nos centraremos en dos aspectos de la interacción a adaptar: los modelos empleados en el reconocimiento de habla, y la incorporación de información específica de cada usuario en el flujo de diálogo. Uno de los módulos de un sistema de diálogo más susceptible de ser contextualizado es el sistema de reconocimiento de habla. Este módulo hace uso de varios modelos para generar una hipótesis de reconocimiento a partir de la señal de habla. En general, un sistema de reconocimiento emplea dos tipos de modelos: uno acústico (que modela cada uno de los fonemas considerados por el reconocedor) y uno lingüístico (que modela las secuencias de palabras que tienen sentido desde el punto de vista de la interacción). En este trabajo contextualizamos el modelo lingüístico del reconocedor de habla, de tal manera que tenga en cuenta la información proporcionada por el usuario, tanto en su intervención actual como en las previas. Estas intervenciones contienen información (semántica y/o discursiva) que puede contribuir a un mejor reconocimiento de las subsiguientes intervenciones del usuario. La estrategia de contextualización propuesta consiste en una adaptación dinámica del modelo de lenguaje empleado en el reconocedor de habla. Dicha adaptación se lleva a cabo mediante una interpolación lineal entre diferentes modelos. En lugar de entrenar los mejores pesos de interpolación, proponemos hacer los mismos dependientes de las condiciones actuales de cada diálogo. El propio sistema obtendrá estos pesos como función de la disponibilidad y relevancia de las diferentes fuentes de información disponibles, tales como los conceptos semánticos extraídos a partir de la intervención del usuario, o las acciones que el mismo desea ejecutar. Uno de los aspectos más comúnmente analizados en la investigación de la Interacción Persona-Máquina es la inclusión de las características específicas de cada usuario en las estructuras de información empleadas por el sistema. El objetivo es tener en cuenta los aspectos que diferencian a cada usuario, de tal manera que el sistema pueda ofrecer a cada uno de ellos el servicio más apropiado (o un mismo servicio, pero de la manera más adecuada a cada usuario). Podemos considerar esta estrategia como una contextualización dependiente del usuario. En este trabajo proponemos la definición de un modelo de usuario que contenga toda la información relativa a cada usuario, que pueda ser potencialmente utilizada por el sistema en un momento determinado de la interacción. En particular, analizaremos aquellas acciones que cada usuario decide ejecutar a lo largo de sus diálogos con el sistema. Nuestro objetivo es determinar cuáles de dichas acciones se convierten en las preferencias de cada usuario. La información de cada usuario quedará representada mediante un vector de características, cada una de las cuales tendrá asociado un valor de confianza. Con ambos elementos proponemos una definición probabilística de una preferencia de uso, como aquella acción cuya verosimilitud es mayor que la del resto de acciones solicitadas por el usuario. A fin de incluir la información dependiente de usuario en el flujo de diálogo, llevamos a cabo una modificación de las estructuras de información en las que se apoya el gestor de diálogo para recuperar información necesaria para resolver ciertos diálogos. En dicha modificación las preferencias de cada usuario pasarán a ser una fuente adicional de información contextual, que será tenida en cuenta por el sistema en aras de una interacción más eficiente (puesto que la nueva fuente de información contribuirá a reducir la necesidad del sistema de solicitar al usuario información adicional, dando lugar en consecuencia a una reducción del número de intervenciones necesarias para llevar a cabo una acción determinada). Para determinar los beneficios de las aplicaciones del marco de contextualización propuesto, llevamos a cabo una evaluación de un sistema de diálogo que incluye las estrategias mencionadas. Hemos recogido diversas métricas, tanto objetivas como subjetivas, que nos permiten determinar las mejoras aportadas por un sistema contextualizado en comparación con el sistema sin contextualizar. De igual manera, hemos recogido las opiniones de los participantes en la evaluación acerca de su percepción del comportamiento del sistema, y de su capacidad de adaptación a las condiciones concretas de cada interacción.

Experiments in abstract interpretation-based code certification for pervasive systems

Proof carrying code (PCC) is a general is originally a roof in ñrst-order logic of certain vermethodology for certifying that the execution of an un- ification onditions and the checking process involves trusted mobile code is safe. The baste idea is that the ensuring that the certifícate is indeed a valid ñrst-order code supplier attaches a certifícate to the mobile code proof. which the consumer checks in order to ensure that the The main practical difñculty of PCC techniques is in code is indeed safe. The potential benefit is that the generating safety certiñeates which at the same time: i) consumer's task is reduced from the level of proving to allow expressing interesting safety properties, ii) can be the level of checking. Recently, the abstract interpre- generated automatically and, iii) are easy and efficient tation techniques developed, in logic programming have to check. In [1], the abstract interpretation techniques been proposed as a basis for PCC. This extended ab- [5] developed in logic programming1 are proposed as stract reports on experiments which illustrate several is- a basis for PCC. They offer a number of advantages sues involved in abstract interpretation-based certifica- for dealing with the aforementioned issues. In particution. First, we describe the implementation of our sys- lar, the xpressiveness of existing abstract domains will tem in the context of CiaoPP: the preprocessor of the be implicitly available in abstract interpretation-based Ciao multi-paradigm programming system. Then, by code certification to deñne a wide range of safety propermeans of some experiments, we show how code certifi- ties. Furthermore, the approach inherits the automation catión is aided in the implementation of the framework. and inference power of the abstract interpretation en- Finally, we discuss the application of our method within gines used in (Constraint) Logic Programming, (C)LP. the área, of pervasive systems

An abstract machine for restricted and-parallel execution of logic programs

Although the sequential execution speed of logic programs has been greatly improved by the concepts introduced in the Warren Abstract Machine (WAM), parallel execution represents the only way to increase this speed beyond the natural limits of sequential systems. However, most proposed parallel logic programming execution models lack the performance optimizations and storage efficiency of sequential systems. This paper presents a parallel abstract machine which is an extension of the WAM and is thus capable of supporting ANDParallelism without giving up the optimizations present in sequential implementations. A suitable instruction set, which can be used as a target by a variety of logic programming languages, is also included. Special instructions are provided to support a generalized version of "Restricted AND-Parallelism" (RAP), a technique which reduces the overhead traditionally associated with the run-time management of variable binding conflicts to a series of simple run-time checks, which select one out of a series of compiled execution graphs.

A system for automatically generating documentation for (C)LP programs

We describe lpdoc, a tool which generates documentation manuals automatically from one or more logic program source files, written in ISO-Prolog, Ciao, and other (C)LP languages. It is particularly useful for documenting library modules, for which it automatically generates a rich description of the module interface. However, it can also be used quite successfully to document full applications. A fundamental advantage of using lpdoc is that it helps maintaining a true correspondence between the program and its documentation, and also identifying precisely to what version of the program a given printed manual corresponds. The quality of the documentation generated can be greatly enhanced by including within the program text assertions (declarations with types, modes, etc.) for the predicates in the program, and machine-readable comments. One of the main novelties of lpdoc is that these assertions and comments are written using the Ciao system assertion language, which is also the language of communication between the compiler and the user and between the components of the compiler. This allows a significant synergy among specification, documentation, optimization, etc. A simple compatibility library allows conventional (C)LP systems to ignore these assertions and comments and treat normally programs documented in this way. The documentation can be generated in many formats including texinfo, dvi, ps, pdf, info, html/css, Unix nroff/man, Windows help, etc., and can include bibliographic citations and images. lpdoc can also generate “man” pages (Unix man page format), nicely formatted plain ascii “readme” files, installation scripts useful when the manuals are included in software distributions, brief descriptions in html/css or info formats suitable for inclusion in on-line indices of manuals, and even complete WWW and info sites containing on-line catalogs of documents and software distributions. The lpdoc manual, all other Ciao system manuals, and parts of this paper are generated by lpdoc.

The ciao prolog system

Ciao is a public domain, next generation multi-paradigm programming environment with a unique set of features: Ciao offers a complete Prolog system, supporting ISO-Prolog, but its novel modular design allows both restricting and extending the language. As a result, it allows working with fully declarative subsets of Prolog and also to extend these subsets (or ISO-Prolog) both syntactically and semantically. Most importantly, these restrictions and extensions can be activated separately on each program module so that several extensions can coexist in the same application for different modules. Ciao also supports (through such extensions) programming with functions, higher-order (with predicate abstractions), constraints, and objects, as well as feature terms (records), persistence, several control rules (breadth-first search, iterative deepening, ...), concurrency (threads/engines), a good base for distributed execution (agents), and parallel execution. Libraries also support WWW programming, sockets, external interfaces (C, Java, TclTk, relational databases, etc.), etc. Ciao offers support for programming in the large with a robust module/object system, module-based separate/incremental compilation (automatically -no need for makefiles), an assertion language for declaring (optional) program properties (including types and modes, but also determinacy, non-failure, cost, etc.), automatic static inference and static/dynamic checking of such assertions, etc. Ciao also offers support for programming in the small producing small executables (including only those builtins used by the program) and support for writing scripts in Prolog. The Ciao programming environment includes a classical top-level and a rich emacs interface with an embeddable source-level debugger and a number of execution visualization tools. The Ciao compiler (which can be run outside the top level shell) generates several forms of architecture-independent and stand-alone executables, which run with speed, efficiency and executable size which are very competive with other commercial and academic Prolog/CLP systems. Library modules can be compiled into compact bytecode or C source files, and linked statically, dynamically, or autoloaded. The novel modular design of Ciao enables, in addition to modular program development, effective global program analysis and static debugging and optimization via source to source program transformation. These tasks are performed by the Ciao preprocessor ( ciaopp, distributed separately). The Ciao programming environment also includes lpdoc, an automatic documentation generator for LP/CLP programs. It processes Prolog files adorned with (Ciao) assertions and machine-readable comments and generates manuals in many formats including postscript, pdf, texinfo, info, HTML, man, etc. , as well as on-line help, ascii README files, entries for indices of manuals (info, WWW, ...), and maintains WWW distribution sites.

An automatic documentation generator for (C)LP - Reference manual

Lpdoc is an automatic program documentation generator for (C)LP systems. Lpdoc generates a reference manual automatically from one or more source files for a logic program (including ISO-Prolog, Ciao, many CLP systems, ...). It is particularly useful for documenting library modules, for which it automatically generates a description of the module interface. However, lpdoc can also be used quite successfully to document full applications and to generate nicely formatted plain ascii "readme" files. A fundamental advantage of using lpdoc to document programs is that it is much easier to maintain a true correspondence between the program and its documentation, and to identify precisely to what version of the program a given printed manual corresponds. The quality of the documentation generated can be greatly enhanced by including within the program text: • assertions (types, modes, etc. ...) for the predicates in the program, and • machine-readable comments (in the "literate programming" style). The assertions and comments included in the source file need to be written using the Ciao system assertion language. A simple compatibility library is available to make traditional (constraint) logic programming systems ignore these assertions and comments allowing normal treatment of programs documented in this way. The documentation is currently generated in HTML or texinf o format. From the texinf o output, printed and on-line manuals in several formats (dvi, ps, info, etc.) can be easily generated automatically, using publicly available tools, lpdoc can also generate 'man' pages (Unix man page format) as well as brief descriptions in html or emacs info formats suitable for inclusion in an on-line index of applications. In particular, lpdoc can create and maintain fully automatically WWW and info sites containing on-line versions of the documents it produces. The lpdoc manual (and the Ciao system manuals) are generated by lpdoc. Lpdoc is distributed under the GNU general public license. Note: lpdoc is fully supported on Linux, Mac OS X, and other Un*x-like systems. Due to the use of several Un*x-related utilities, some documentation back-ends may require Cygwin under Win32. This documentation corresponds to version 3.0 (2011/7/7, 16:33:15 CEST).

An abstract machine based execution model for computer architecture design and efficient implementation of logic programs in parallel.

The term "Logic Programming" refers to a variety of computer languages and execution models which are based on the traditional concept of Symbolic Logic. The expressive power of these languages offers promise to be of great assistance in facing the programming challenges of present and future symbolic processing applications in Artificial Intelligence, Knowledge-based systems, and many other areas of computing. The sequential execution speed of logic programs has been greatly improved since the advent of the first interpreters. However, higher inference speeds are still required in order to meet the demands of applications such as those contemplated for next generation computer systems. The execution of logic programs in parallel is currently considered a promising strategy for attaining such inference speeds. Logic Programming in turn appears as a suitable programming paradigm for parallel architectures because of the many opportunities for parallel execution present in the implementation of logic programs. This dissertation presents an efficient parallel execution model for logic programs. The model is described from the source language level down to an "Abstract Machine" level suitable for direct implementation on existing parallel systems or for the design of special purpose parallel architectures. Few assumptions are made at the source language level and therefore the techniques developed and the general Abstract Machine design are applicable to a variety of logic (and also functional) languages. These techniques offer efficient solutions to several areas of parallel Logic Programming implementation previously considered problematic or a source of considerable overhead, such as the detection and handling of variable binding conflicts in AND-Parallelism, the specification of control and management of the execution tree, the treatment of distributed backtracking, and goal scheduling and memory management issues, etc. A parallel Abstract Machine design is offered, specifying data areas, operation, and a suitable instruction set. This design is based on extending to a parallel environment the techniques introduced by the Warren Abstract Machine, which have already made very fast and space efficient sequential systems a reality. Therefore, the model herein presented is capable of retaining sequential execution speed similar to that of high performance sequential systems, while extracting additional gains in speed by efficiently implementing parallel execution. These claims are supported by simulations of the Abstract Machine on sample programs.

A Satisfaction-based Model for Affect Recognition from Conversational Features in Spoken Dialog Systems

Detecting user affect automatically during real-time conversation is the main challenge towards our greater aim of infusing social intelligence into a natural-language mixed-initiative High-Fidelity (Hi-Fi) audio control spoken dialog agent. In recent years, studies on affect detection from voice have moved on to using realistic, non-acted data, which is subtler. However, it is more challenging to perceive subtler emotions and this is demonstrated in tasks such as labelling and machine prediction. This paper attempts to address part of this challenge by considering the role of user satisfaction ratings and also conversational/dialog features in discriminating contentment and frustration, two types of emotions that are known to be prevalent within spoken human-computer interaction. However, given the laboratory constraints, users might be positively biased when rating the system, indirectly making the reliability of the satisfaction data questionable. Machine learning experiments were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. Our results indicated that standard classifiers were significantly more successful in discriminating the abovementioned emotions and their intensities (reflected by user satisfaction ratings) from annotator data than from user data. These results corroborated that: first, satisfaction data could be used directly as an alternative target variable to model affect, and that they could be predicted exclusively by dialog features. Second, these were only true when trying to predict the abovementioned emotions using annotator?s data, suggesting that user bias does exist in a laboratory-led evaluation.

Assessing user bias in affect detection within context-based spoken dialog systems

This paper presents an empirical evidence of user bias within a laboratory-oriented evaluation of a Spoken Dialog System. Specifically, we addressed user bias in their satisfaction judgements. We question the reliability of this data for modeling user emotion, focusing on contentment and frustration in a spoken dialog system. This bias is detected through machine learning experiments that were conducted on two datasets, users and annotators, which were then compared in order to assess the reliability of these datasets. The target used was the satisfaction rating and the predictors were conversational/dialog features. Our results indicated that standard classifiers were significantly more successful in discriminating frustration and contentment and the intensities of these emotions (reflected by user satisfaction ratings) from annotator data than from user data. Indirectly, the results showed that conversational features are reliable predictors of the two abovementioned emotions.