MORPH: A Reference Architecture for Configuration and Behaviour Self-Adaptation

An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus, dynamic reconfiguration and discrete event control theory are at the heart of architectural adaptation. Although controlling configuration and behaviour at runtime has been discussed and applied to architectural adaptation, architectures for self-adaptive systems often compound these two aspects reducing the potential for adaptability. In this paper we propose a reference architecture that allows for coordinated yet transparent and independent adaptation of system configuration and behaviour

Celebrating 70: An Interview with Don Berry

Donald (Don) Arthur Berry, born May 26, 1940 in Southbridge, Massachusetts, earned his A.B. degree in mathematics from Dartmouth College and his M.A. and Ph.D. in statistics from Yale University. He served first on the faculty at the University of Minnesota and subsequently held endowed chair positions at Duke University and The University of Texas M.D. Anderson Center. At the time of the interview he served as Head of the Division of Quantitative Sciences, and Chairman and Professor of the Department of Biostatistics at UT M.D. Anderson Center.Comment: Published in at http://dx.doi.org/10.1214/11-STS366 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Accuracy and consistency of grass pollen identification by human analysts using electron micrographs of surface ornamentation

• Premise of the study: Humans frequently identify pollen grains at a taxonomic rank above species. Grass pollen is a classic case of this situation, which has led to the development of computational methods for identifying grass pollen species. This paper aims to provide context for these computational methods by quantifying the accuracy and consistency of human identification. • Methods: We measured the ability of nine human analysts to identify 12 species of grass pollen using scanning electron microscopy images. These are the same images that were used in computational identifications. We have measured the coverage, accuracy, and consistency of each analyst, and investigated their ability to recognize duplicate images. • Results: Coverage ranged from 87.5% to 100%. Mean identification accuracy ranged from 46.67% to 87.5%. The identification consistency of each analyst ranged from 32.5% to 87.5%, and each of the nine analysts produced considerably different identification schemes. The proportion of duplicate image pairs that were missed ranged from 6.25% to 58.33%. • Discussion: The identification errors made by each analyst, which result in a decline in accuracy and consistency, are likely related to psychological factors such as the limited capacity of human memory, fatigue and boredom, recency effects, and positivity bias

Intelligence in Light of Perspectivalism: Lessons from Octopus Intelligence and Artificial Intelligence

This paper pursues the question of where we stand today in making sense of "intelligence". Even though definitions of intelligence have been provided over many years in different fields and disciplines such as psychology, neuroscience, and computer science, these crude approaches often turn out to be overly systematic, rigid, and reductive. Moreover, as we argue here, much work on intelligence suffers from the bias of using humans as a yardstick and/or of focusing on human intelligence at the expense of acknowledging other, i.e., non-human forms of intelligence. By means of a concise literature review and case study analysis, the objective of this paper is to pave the ground for overcoming our anthropocentrism and appreciating the wonders of intelligence in nonhuman and non-biological animals instead. For that reason, we study two cases of octopus intelligence and intelligence in machine learning systems to embrace the notion of intelligence as a non-unitary faculty with pluralistic forms. Furthermore, we derive lessons for advancing our human self-understanding

ASPIRE Adaptive strategy prediction in a RTS environment

When playing a Real Time Strategy(RTS) game against the non-human player(bot) it is important that the bot can do different strategies to create a challenging experience over time. In this thesis we aim to improve the way the bot can predict what strategies the player is doing by analyzing the replays of the given players games. This way the bot can change its strategy based upon the known knowledge of the game state and what strategies the player have used before. We constructed a Bayesian Network to handle the predictions of the opponent's strategy and inserted that into a preexisting bot. Based on the results from our experiments we can state that the Bayesian Network adapted to the strategies our bot was exposed to. In addition we can see that the Bayesian Network only predicted the possible strategies given the obtained information about the game state.INFO390MASV-INF

Constructive expertise: a critical, ecological and micro-developmental perspective on developing talent

A multitude of performance domains pursue the goal of understanding how we develop talent and expertise. Therefore, the main objective of the present work was to embrace this pursuit whilst operating in a sporting context. The work initially adopted an exploratory, critical and investigative approach to the problem with the remaining series of studies emerging from these initial findings. Study 1 utilised ethnographic enquiry over an eighteen month period whilst working in collaboration with the Rugby Football Union Elite Referee Unit. The study found shifts in existing perspectives of expertise and talent development including a) the movement from a descriptive and phase-staged approach to one which is dynamic and non-linear, b) nonnormative as well as normative influences, c) recognition of an 'expert self as intrapersonal, interpersonal, group and social, d) expertise development existing at micro-, meso- and macrodevelopment levels, e) an integrative, contextualised and multiplicative nature of expertise, f) emergent as well as planned development, g) identification of a 'nested' and ecological outlook of expertise acknowledging the necessity of a positive 'talent development environment'. Additionally, mechanisms of expertise expanded on the existing theory of deliberate practice to include 'deliberate experience' and 'transfer of skills'. In sum- study 1 encountered an approach to expertise which embraced complexity and paradox, was equally psycho-social dynamic than intrapersonal and fostered the necessity for a creation of contexts from which elite performance can morph. From these findings, and alternative studies and readings, a period of reflection occurred where models of 'non-linear and dynamical systems', 'talent development environments', 'adaptive expertise', 'fractal models' and the promotion of adaptive expertise, self-regulation and meta-cognitive skills required to negotiate the complex pathway associated with eminent performance was explored before a final sense-making notion of 'expertise as constructivism' was embraced. The remainder of the work embraced this constructivist approach of expertise and talent development which was then researched in collaboration with the Scottish Small-Bore Shooting team over a two year period. The period of work embraced 'constructivism as action research'. Study 2 utilised an 'ecological task analysis' of the Scottish Small Bore Shooting team and its members to identify constraints and affordances of excellence. It also served as a benchmark of existing levels of expertise which were evaluated at the end of the action research. Study 3 served as the primary research study and assessed the overall efficacy of the constructivist developmental approach inclusive of major transition processes over the two year period as served by the constructivist design. The program was deemed successful in relation to performance outcomes at the 2006 Melbourne Commonwealth Games. Study 4 focused on the importance of creating constructivist 'talent development environments' in comparison to an existing work of literature. Findings suggest a constructivist talent development environment which attends to both the planned and emergent nature of expertise requires fostering. Finally, a theoretical model of constructivist expertise and talent development is offered encompassing the overall findings of the work

GoalD: A Goal-Driven Deployment Framework for Dynamic and Heterogeneous Computing Environments

Context: Emerging paradigms like Internet of Things and Smart Cities utilize advanced sensing and communication infrastructures, where heterogeneity is an inherited feature. Applications targeting such environments require adaptability and context-sensitivity to uncertain availability and failures in resources and their ad-hoc networks. Such heterogeneity is often hard to predict, making the deployment process a challenging task. Objective: This paper proposes GoalD as a goal-driven framework to support autonomous deployment of heterogeneous computational resources to fulfill requirements, seen as goals, and their correlated components on one hand, and the variability space of the hosting computing and sensing environment on the other hand. Method: GoalD comprises an offline and an online stage to fulfill autonomous deployment by leveraging the use of goals. Deployment configuration strategies arise from the variability structure of the Contextual Goal Model as an underlying structure to guide autonomous planning by selecting available as well as suitable resources at runtime. Results: We evaluate GoalD on an existing exemplar from the selfadaptive systems community – the Tele Assistance Service provided by Weyns and Calinescu [1]. Furthermore, we evaluate the scalability of GoalD on a repository consisting of 430,500 artifacts. The evaluation results demonstrate the usefulness and scalability of GoalD in planning the deployment of a system with thousands of components in a few milliseconds

Cognitive interconnections

Introduction. Originally conceived as a non-commercial infrastructure, the Internet has gradually morphed into the largest ‘connectivity machine’ ever built. Business, entertainment, social life and politics are heavily reliant on the Web, which in turn requires a fully-operational network. Yet, unlike any other complex machine, the Internet has not been built with the knowledge of what it was later supposed to be doing. So now, many worry that it will fail under the strain of time- and dataintensive applications. HD Video, Cloud Services and the Internet of Things are already making this issue apparent. What will happen when new applications that are not yet in sight emerge? In this lecture I will explain why the time is ripe for a complete overhaul of the net, highlighting its actual flaws. I will discuss the network mechanisms that will help to shape the next-generation Internet, focusing on the prospects and hurdles of ‘cognitive’ networking