Exploring adaptation & self-adaptation in autonomic computing systems

This panel paper sets out to discuss what self-adaptation means, and to explore the extent to which current autonomic systems exhibit truly self-adaptive behaviour. Many of the currently cited examples are clearly adaptive, but debate remains as to what extent they are simply following prescribed adaptation rules within preset bounds, and to what extent they have the ability to truly learn new behaviour. Is there a standard test that can be applied to differentiate? Is adaptive behaviour sufficient anyway? Other autonomic computing issues are also discussed

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

The evolutionary origins of volition

It appears to be a straightforward implication of distributed cognition principles that there is no integrated executive control system (e.g. Brooks 1991, Clark 1997). If distributed cognition is taken as a credible paradigm for cognitive science this in turn presents a challenge to volition because the concept of volition assumes integrated information processing and action control. For instance the process of forming a goal should integrate information about the available action options. If the goal is acted upon these processes should control motor behavior. If there were no executive system then it would seem that processes of action selection and performance couldn’t be functionally integrated in the right way. The apparently centralized decision and action control processes of volition would be an illusion arising from the competitive and cooperative interaction of many relatively simple cognitive systems. Here I will make a case that this conclusion is not well-founded. Prima facie it is not clear that distributed organization can achieve coherent functional activity when there are many complex interacting systems, there is high potential for interference between systems, and there is a need for focus. Resolving conflict and providing focus are key reasons why executive systems have been proposed (Baddeley 1986, Norman and Shallice 1986, Posner and Raichle 1994). This chapter develops an extended theoretical argument based on this idea, according to which selective pressures operating in the evolution of cognition favor high order control organization with a ‘highest-order’ control system that performs executive functions

An interoceptive predictive coding model of conscious presence

We describe a theoretical model of the neurocognitive mechanisms underlying conscious presence and its disturbances. The model is based on interoceptive prediction error and is informed by predictive models of agency, general models of hierarchical predictive coding and dopaminergic signaling in cortex, the role of the anterior insular cortex (AIC) in interoception and emotion, and cognitive neuroscience evidence from studies of virtual reality and of psychiatric disorders of presence, specifically depersonalization/derealization disorder. The model associates presence with successful suppression by top-down predictions of informative interoceptive signals evoked by autonomic control signals and, indirectly, by visceral responses to afferent sensory signals. The model connects presence to agency by allowing that predicted interoceptive signals will depend on whether afferent sensory signals are determined, by a parallel predictive-coding mechanism, to be self-generated or externally caused. Anatomically, we identify the AIC as the likely locus of key neural comparator mechanisms. Our model integrates a broad range of previously disparate evidence, makes predictions for conjoint manipulations of agency and presence, offers a new view of emotion as interoceptive inference, and represents a step toward a mechanistic account of a fundamental phenomenological property of consciousness

A specification method for the scalable self-governance of complex autonomic systems

IBM, amongst many others, have sought to endow computer systems with selfmanagement capabilities by delegating vital functions to the software itself and proposed the Autonomic Computing model. Hence inducing the so-called self-* properties including the system's ability to be self-configuring, self-optimising, self-healing and self-protecting. Initial attempts to realise such a vision have so far mostly relied on a passive adaptation whereby Design by Contract and Event-Condition-Action (ECA) type constructs are used to regulate the target systems behaviour: When a specific event makes a certain condition true then an action is triggered which executes either within the system or on its environment Whilst, such a model works well for closed systems, its effectiveness and applicability of approach diminishes as the size and complexity of the managed system increases, necessitating frequent updates to the ECA rule set to cater for new and/or unforeseen systems' behaviour. More recent research works are now adopting the parametric adaptation model, where the events, conditions and actions may be adjusted at runtime in response to the system's observed state. Such an improved control model works well up to a point, but for large scale systems of systems, with very many component interactions, the predictability and traceability of the regulation and its impact on the whole system is intractable. The selforganising systems theory, however, offers a scaleable alternative to systems control utilising emerging behaviour, observed at a global level, resulting from the low-level interactions of the distributed components. Whereby, for instance, key signals (signs) for ECA style feedback control need no longer be recognised or understood in the context of the design time system but are defined by their relevance to the runtime system. Nonetheless this model still suffers from a usually inaccessible control model with no intrinsic meaning assigned to data extraction from the systems operation. In other words, there is no grounded definition of particular observable events occurring in the system. This condition is termed the Signal Grounding Problem. This problem cannot usually be solved by analytical or algorithmic methods, as these solutions generally require precise problem formulations and a static operating domain. Rather cognitive techniques will be needed that perform effectively to evaluate and improve performance in the presence of complex, incomplete, dynamic and evolving environments. In order to develop a specification method for scalable self-governance of autonomic systems of systems, this thesis presents a number of ways to alleviate, or circumvent, the Signal Grounding Problem through the utilisation of cognitive systems and the properties of complex systems. After reviewing the specification methods available for governance models, the Situation Calculus dialect of first order logic is described with the necessary modalities for the specification of deliberative monitoring in partially observable environments with stochastic actions. This permits a specification method that allows the depiction of system guards and norms, under central control, as well as the deliberative functions required for decentralised components to present techniques around the Signal Grounding problem, engineer emergence and generally utilise the properties of large complex systems for their own self-governance. It is shown how these large-scale behaviours may be implemented and the properties assessed and utilised by an Observer System through fully functioning implementations and simulations. The work concludes with two case studies showing how the specification would be achieved in practice: An observer based meta-system for a decision support system in medicine is described, specified and implemented up to parametric adaptation and a NASA project is described with a specification given for the interactions and cooperative behaviour that leads to scale-free connectivity, which the observer system may then utilise for a previously described efficient monitoring strategy

Artificial intelligence based ECG signal classification of sendetary, smokers and athletes

The current study deals with the design of a computer aided diagnosis procedure to classify 3 groups of people with different lifestyles, namely sedentary, smoker and athletes. The ECG Classification based on statistical analysis of HRV and ECG features. The heart rate variability (HRV) parameters and ECG statistical features were used for the pattern recognition in Artificial Intelligence classifiers. The ECG was recorded for a particular time duration using the EKG sensor. The HRV, time domain and wavelet parameters were calculated using NI BIOMEDICAL STARTUP KIT 3.0 and LABVIEW 2010. The important HRV features, time domain and wavelet features were calculated by the statistical non-linear classifiers (CART and BT).the important parameters were fed as input to artificial intelligence classifiers like ANN and SVM. The Artificial Intelligence classifiers like artificial neural network (ANN) and Support vector Machine (SVM) were used to classify 60 numbers of ECG signal. It was observed from result that the Multi layer perceptron (MLP) based ANN classifier gives an accuracy of 95%, which is highest among other the classifiers. The HRV study implies that the time domain parameters (RMSSD and PNN50), frequency domain parameters (HF power and LF/HF peak), Poincare parameter (SD1) and geometric parameters (RR triangular index and TINN) are higher in athlete class and lower in smoker class. The Higher values of HRV parameters indicate increase in parasympathetic activity and decrease in sympathetic activity of the ANS. This indicates that the athlete class has better heath and less chance of cardiovascular diseases where smoker class has high chances of cardiovascular diseases. These HRV parameters of sedentary class were higher than smoker class but lower than athlete class. This indicates less chances of cardiovascular disease in sedentary class as compared to smoker class

Rail Internet of Things: An Architectural Platform and Assured Requirements Model

Given the plethora of individual preferences and requirements of public transport passengers for travel, seating, catering, etc., it becomes very challenging to tailor generic services to individuals’ requirements using the existing service platforms. As tens of thousands of sensors have been already deployed along roadsides and rail tracks, and on buses and trains in many countries, it is expected that the introduction of IP networking will revolutionise the functionality of public transport in general and rail services in particular. In this paper, we propose a new communication paradigm to improve rail services and address the requirement of rail service users: the Rail Internet of Things (RIoT). To the best of our knowledge, it is the first work to define the RIoT and design an architectural platform that includes its components and the data communication channels. Moreover, we develop an assured requirements model using the situation calculus modelling to represent the fundamental requirements for adjustable, decentralised feedback control mechanisms necessary for the RIoT-ready software systems. The developed formal model is applied to demonstrate the design of passenger assistance software that interacts with the RIoT ecosystem and provides passengers with real-time information that is tailored to their requirements with runtime adaptability. Keywords—Assistance; Assured model; Inclusive; IoT; Rail Internet of Things (RIoT); Situation Calculu

Psychophysiology in games

Psychophysiology is the study of the relationship between psychology and its physiological manifestations. That relationship is of particular importance for both game design and ultimately gameplaying. Players’ psychophysiology offers a gateway towards a better understanding of playing behavior and experience. That knowledge can, in turn, be beneficial for the player as it allows designers to make better games for them; either explicitly by altering the game during play or implicitly during the game design process. This chapter argues for the importance of physiology for the investigation of player affect in games, reviews the current state of the art in sensor technology and outlines the key phases for the application of psychophysiology in games.The work is supported, in part, by the EU-funded FP7 ICT iLearnRWproject (project no: 318803).peer-reviewe

e-Business challenges and directions: important themes from the first ICE-B workshop

A three-day asynchronous, interactive workshop was held at ICE-B’10 in Piraeus, Greece in July of 2010. This event captured conference themes for e-Business challenges and directions across four subject areas: a) e-Business applications and models, b) enterprise engineering, c) mobility, d) business collaboration and e-Services, and e) technology platforms. Quality Function Deployment (QFD) methods were used to gather, organize and evaluate themes and their ratings. This paper summarizes the most important themes rated by participants: a) Since technology is becoming more economic and social in nature, more agile and context-based application develop methods are needed. b) Enterprise engineering approaches are needed to support the design of systems that can evolve with changing stakeholder needs. c) The digital native groundswell requires changes to business models, operations, and systems to support Prosumers. d) Intelligence and interoperability are needed to address Prosumer activity and their highly customized product purchases. e) Technology platforms must rapidly and correctly adapt, provide widespread offerings and scale appropriately, in the context of changing situational contexts