Temporal Models For History-Aware Explainability In Self-Adaptive Systems

The complexity of real-world problems requires modern software systems to be able to autonomously adapt and modify their behaviour at runtime to deal with unforeseen internal and external fluctuations and contexts. Consequently, these self-adaptive systems (SAS) can show unexpected and surprising behaviours which stakeholders may not understand or agree with. This may be exacerbated due to the ubiquity and complexity of Artificial Intelligence (AI) techniques which are often considered “black boxes” and are increasingly used by SAS. This thesis explores how synergies between model-driven engineering and runtime monitoring help to enable explanations based on SAS’ historical behaviour with the objective of promoting transparency and understandability in these types of systems. Specifically, this PhD work has studied how the use of runtime models extended with long-term memory can provide the abstraction, analysis and reasoning capabilities needed to support explanations when using AI-based SAS. For this purpose, this work argues that a system should i) offer access and retrieval of historical data about past behaviour, ii) track over time the reasons for its decision making, and iii) be able to convey this knowledge to different stakeholders as part of explanations for justifying its behaviour. Runtime models stored in Temporal Graph Databases, which result in Temporal Models (TMs), are proposed for tracking the decision-making history of SAS to support explanations. The approach enables explainability for interactive diagnosis (i.e. during execution) and forensic analysis (i.e. after the fact) based on the trajectory of the SAS execution. Furthermore, in cases where the resources are limited (e.g., storage capacity or time to response), the proposed architecture also integrates the runtime monitoring technique, complex event processing (CEP). CEP allows detecting matches to event patterns that need to be stored instead of keeping the entire history. The proposed architecture helps developers in gaining insights into SAS while they work on validating and improving their systems

Temporal Models for History-Aware Explainability

On one hand, there has been a growing interest towards the application of AI-based learning and evolutionary programming for self-adaptation under uncertainty. On the other hand, self-explanation is one of the self-* properties that has been neglected. This is paradoxical as self-explanation is inevitably needed when using such techniques. In this paper, we argue that a self-adaptive autonomous system (SAS) needs an infrastructure and capabilities to be able to look at its own history to explain and reason why the system has reached its current state. The infrastructure and capabilities need to be built based on the right conceptual models in such a way that the system's history can be stored, queried to be used in the context of the decision-making algorithms. The explanation capabilities are framed in four incremental levels, from forensic self-explanation to automated history-aware (HA) systems. Incremental capabilities imply that capabilities at Level n should be available for capabilities at Level n + 1. We demonstrate our current reassuring results related to Level 1 and Level 2, using temporal graph-based models. Specifically, we explain how Level 1 supports forensic accounting after the system's execution. We also present how to enable on-line historical analyses while the self-adaptive system is running, underpinned by the capabilities provided by Level 2. An architecture which allows recording of temporal data that can be queried to explain behaviour has been presented, and the overheads that would be imposed by live analysis are discussed. Future research opportunities are envisioned

On the design of a native Zero-touch 6G architecture

The complexity of envisioned 6G telecommunication networks requires an intrinsically intelligent architecture designed to autonomously adapt to dynamics with end-to-end zero-touch service automation operations. Motivated by this vision, this paper tries to formulate concepts and solution aspects towards designing a native Zero-touch 6G architecture. Our discussion concentrates around three main pillars, i.e. (i) introducing Machine Learning (ML) models in the core design of the 6G architecture as native functions rather than add-on model solutions; (ii) distributing 6G functionality to different components up to the extreme edge; to (iii) leverage technology leaps enabling, e.g., the use of multi-access technologies and peer-topeer communications besides the standard cellular connectivity and other centralised functionalit

Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning

Modern software systems are increasingly expected to show higher degrees of autonomy and self-management to cope with uncertain and diverse situations. As a consequence, autonomous systems can exhibit unexpected and surprising behaviours. This is exacerbated due to the ubiquity and complexity of Artificial Intelligence (AI)-based systems. This is the case of Reinforcement Learning (RL), where autonomous agents learn through trial-and-error how to find good solutions to a problem. Thus, the underlying decision-making criteria may become opaque to users that interact with the system and who may require explanations about the system’s reasoning. Available work for eXplainable Reinforcement Learning (XRL) offers different trade-offs: e.g. for runtime explanations, the approaches are model-specific or can only analyse results after-the-fact. Different from these approaches, this paper aims to provide an online model-agnostic approach for XRL towards trustworthy and understandable AI. We present ETeMoX, an architecture based on temporal models to keep track of the decision-making processes of RL systems. In cases where the resources are limited (e.g. storage capacity or time to response), the architecture also integrates complex event processing, an event-driven approach, for detecting matches to event patterns that need to be stored, instead of keeping the entire history. The approach is applied to a mobile communications case study that uses RL for its decision-making. In order to test the generalisability of our approach, three variants of the underlying RL algorithms are used: Q-Learning, SARSA and DQN. The encouraging results show that using the proposed configurable architecture, RL developers are able to obtain explanations about the evolution of a metric, relationships between metrics, and were able to track situations of interest happening over time windows

Intelligent PillBox: Automatic and Programmable Assistive Technology Device

Assistive Technology (AT) maintains and improves the individual's functioning and independence, thereby promoting their well-being. But today only 1 from each 10 people in need have access to AT due to high costs and a lack of awareness, availability, personal training, policy and financing. By 2050, more than 2 billion people will need at least 1 assistive product with many elderly needing 2 or more. Elderly make important contributions to the society. Though some people aged well, other become frail, with a high risk of disease. In this paper, we propose a first approach related the design of AT device. This uses open source technologies and gives a new choice in taking medication dosages. "The Intelligent PillBox" allows the organization of several medication schedules that health disorders presented in elderly need basically. Arduino Mega 2560 was took as the principal controller. This prototype contains; a programmable alarm system with an automatic opening and closing system, an interactive user interface and a notification system through GSM network. The development of this device is focused in the support of elderly people and other vulnerable groups that may need for an assisted care.Innsbruc

Towards an architecture integrating complex event processing and temporal graphs for service monitoring

Software is becoming more complex as it needs to deal with an increasing number of aspects in volatile environments. This complexity may cause behaviors that violate the imposed constraints. A goal of runtime service monitoring is to determine whether the service behaves as intended to potentially allow the correction of the behavior. It may be set up in advance the infrastructure to allow the detections of suspicious situations. However, there may also be unexpected situations to look for as they only become evident during data stream monitoring at runtime produced by te system. The access to historic data may be key to detect relevant situations in the monitoring infrastructure. Available technologies used for monitoring offer different trade-offs, e.g. in cost and flexibility to store historic information. For instance, Temporal Graphs (TGs) can store the long-term history of an evolving system for future querying, at the expense of disk space and processing time. In contrast, Complex Event Processing (CEP) can quickly react to incoming situations efficiently, as long as the appropriate event patterns have been set up in advance. This paper presents an architecture that integrates CEP and TGs for service monitoring through the data stream produced at runtime by a system. The pros and cons of the proposed architecture for extracting and treating the monitored data are analyzed. The approach is applied on the monitoring of Quality of Service (QoS) of a data-management network case study. It is demonstrated how the architecture provides rapid detection of issues, as well as the ability to access to historical data about the state of the system to allow for a comprehensive monitoring solution

Diseño e implementación de un prototipo de pastillero digital para la toma de medicación de pacientes adultos mayores, mediante la integración de nuevas tecnologías de hardware y software libre

La tecnología asistiva (Assistive Technology - AT) mantiene y mejora el funcionamiento y promueve la independencia del individuo, mejorando su bienestar y calidad de vida. Actualmente solo una de cada diez personas con necesidad de algún tipo de asistencia, tienen acceso a AT debido a los altos costos, falta de conciencia, disponibilidad, capacitación personal, políticas y financiamiento. Para 2050, más de dos mil millones de personas necesitarán al menos un producto de asistencia y muchos adultos mayores necesitarán dos o más. Aunque algunas personas envejecen saludablemente, otras presentan quebrantos en su salud. En este trabajo, se propone una aproximación incial relacionada al diseño de un dispositivo AT. Para ello, se hace uso de tecnologías de código abierto que ofrecen una nueva alternativa en la toma de dosis de medicamentos. El “Intelligent Pillbox", el cual constituye nuestra propuesta, permite organizar varios esquemas de medicación para los trastornos de salud, que enfrentan los pacientes de la tercera edad. Este prototipo contiene una alarma programable, un sistema automático de apertura y cierre, un sistema de interfaz de usuario interactiva, un sistema de notificación a través de la red GSM y además utiliza un microcontrolador Arduino Mega 2560 para el control total del dispositivo.Assistive Technology (AT) maintains and improves the individual’s functioning and independence, thereby promoting their well-being. But today only 1 from each 10 people in need have access to AT due to high costs and a lack of awareness, availability, personal training, policy and financing. By 2050, more than 2 billion people will need at least 1 assistive product with many elderly needing 2 or more. Elderly make important contributions to the society. Though some people aged well, other become frail, with a high risk of disease. In this paper, we propose a first approach related the design of AT device. This uses open source technologies and gives a new choice in taking medication dosages. “The Intelligent PillBox” allows the organization of several medication schedules that health disorders presented in elderly need basically. Arduino Mega 2560 was took as the principal controller. This prototype contains; a programmable alarm system with an automatic opening and closing system, an interactive user interface and a notification system through GSM network. The development of this device is focused in the support of elderly people and other vulnerable groups that may need for an assisted care.Ingeniero en Electrónica y TelecomunicacionesCuenc