Showing papers on "Adaptation (computer science) published in 2008"

The Art of Multiprocessor Programming

Abstract: Computer architecture is about to undergo, if not another revolution, then a vigorous shaking-up. The major chip manufacturers have, for the time being, simply given up trying to make processors run faster. Instead, they have recently started shipping "multicore" architectures, in which multiple processors (cores) communicate directly through shared hardware caches, providing increased concurrency instead of increased clock speed.As a result, system designers and software engineers can no longer rely on increasing clock speed to hide software bloat. Instead, they must somehow learn to make effective use of increasing parallelism. This adaptation will not be easy. Conventional synchronization techniques based on locks and conditions are unlikely to be effective in such a demanding environment. Coarse-grained locks, which protect relatively large amounts of data, do not scale, and fine-grained locks introduce substantial software engineering problem.Transactional memory is a computational model in which threads synchronize by optimistic, lock-free transactions. This synchronization model promises to alleviate many (not all) of the problems associated with locking, and there is a growing community of researchers working on both software and hardware support for this approach. This talk will survey the area, with a focus on open research problems.

The role of local institutions in adaptation to climate change

Abstract: This paper examines the relationships between climate-related vulnerabilities, adaptation practices, institutions, and external interventions to show the role and importance of local institutions in climate change. The increasing attention to adaptation to climate change has not come with sufficient emphasis on the local nature of climate adaptation and on the role of local institutions and local governance in shaping adaptation practices. This paper presents two research projects on adaptation and institutions at the World Bank which aim to illuminate precisely these existing lacunae in theoretical and practical knowledge about adaptation. Focusing on the linkages between adaptation strategies and institutions, the first study shows the critical role institutions play in determining the nature and outcomes of adaptation strategies in a territorial development context and will try to demonstrate how past decentralized and area-based approaches on local development could be used to strengthen local adaptive capacity and resilience to climate change related risks. The second study focuses on an assessment of the relative costs and benefits of different adaptation responses related to a subset of climate hazards (particularly droughts and erratic rainfall), and the role of institutions in reducing the costs of adaptation.

Humans : Still Vital After All These Years of Automation

Abstract: OBJECTIVE: The authors discuss empirical studies of human-automation interaction and their implications for automation design. BACKGROUND: Automation is prevalent in safety-critical systems and increasingly in everyday life. Many studies of human performance in automated systems have been conducted over the past 30 years. METHODS: Developments in three areas are examined: levels and stages of automation, reliance on and compliance with automation, and adaptive automation. RESULTS: Automation applied to information analysis or decision-making functions leads to differential system performance benefits and costs that must be considered in choosing appropriate levels and stages of automation. Human user dependence on automated alerts and advisories reflects two components of operator trust, reliance and compliance, which are in turn determined by the threshold designers use to balance automation misses and false alarms. Finally, adaptive automation can provide additional benefits in balancing workload and maintaining the user's situation awareness, although more research is required to identify when adaptation should be user controlled or system driven. CONCLUSIONS: The past three decades of empirical research on humans and automation has provided a strong science base that can be used to guide the design of automated systems. APPLICATION: This research can be applied to most current and future automated systems. Language: en

User—robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy

Abstract: This paper describes a hands-off socially assistive therapist robot designed to monitor, assist, encourage, and socially interact with post-stroke users engaged in rehabilitation exercises. We investigate the role of the robot’s personality in the hands-off therapy process, focusing on the relationship between the level of extroversion–introversion of the robot and the user. We also demonstrate a behavior adaptation system capable of adjusting its social interaction parameters (e.g., interaction distances/proxemics, speed, and vocal content) toward customized post-stroke rehabilitation therapy based on the user’s personality traits and task performance. Three validation experiment sets are described. The first maps the user’s extroversion–introversion personality dimension to a spectrum of robot therapy styles that range from challenging to nurturing. The second and the third experiments adjust the personality matching dynamically to adapt the robot’s therapy styles based on user personality and performance. The reported results provide first evidence for user preference for personality matching in the assistive domain and demonstrate how the socially assistive robot’s autonomous behavior adaptation to the user’s personality can result in improved human task performance.

Resilience, an Evolving Concept: A Review of Literature Relevant to Aboriginal Research

Abstract: Resilience has been most frequently defined as positive adaptation despite adversity. Over the past 40 years, resilience research has gone through several stages. From an initial focus on the invulnerable or invincible child, psychologists began to recognize that much of what seems to promote resilience originates outside of the individual. This led to a search for resilience factors at the individual, family, community - and, most recently, cultural - levels. In addition to the effects that community and culture have on resilience in individuals, there is growing interest in resilience as a feature of entire communities and cultural groups. Contemporary researchers have found that resilience factors vary in different risk contexts and this has contributed to the notion that resilience is a process. In order to characterize the resilience process in a particular context, it is necessary to identify and measure the risk involved and, in this regard, perceived discrimination and historical trauma are part of the context in many Aboriginal communities. Researchers also seek to understand how particular protective factors interact with risk factors and with other protective factors to support relative resistance. For this purpose they have developed resilience models of three main types: "compensatory," "protective," and "challenge" models. Two additional concepts are resilient reintegration, in which a confrontation with adversity leads individuals to a new level of growth, and the notion endorsed by some Aboriginal educators that resilience is an innate quality that needs only to be properly awakened.The review suggests five areas for future research with an emphasis on youth: 1) studies to improve understanding of what makes some Aboriginal youth respond positively to risk and adversity and others not; 2) case studies providing empirical confirmation of the theory of resilient reintegration among Aboriginal youth; 3) more comparative studies on the role of culture as a resource for resilience; 4) studies to improve understanding of how Aboriginal youth, especially urban youth, who do not live in self-governed communities with strong cultural continuity can be helped to become, or remain, resilient; and 5) greater involvement of Aboriginal researchers who can bring a nonlinear world view to resilience research.

Designing Organizations that Design Environments: Lessons from Entrepreneurial Expertise

Abstract: Human artifacts lie on the interface between their inner environments and their outer environments. Organizations, therefore, are apt subjects to be studied through a science of the artificial. Furthermore, organizational design happens at two interfaces: first, at the interface between organizational founder(s) and the firms they design, and second, between the firms and the environments in which they operate. We use recent developments in the study of entrepreneurial expertise to show why an effectual logic of design is necessary at the first interface, and what its consequences are for designing at the second. In particular, we use the exemplar case of Starbucks to codify three key characteristics of the design problem at the first interface — namely, Knightian uncertainty, goal ambiguity and environmental isotropy. We then use an `alternate histories' method to trace four strategic options — namely, planning, adaptation, vision and transformation — for designing at the second interface. In the final a...

Reach Adaptation: What Determines Whether We Learn an Internal Model of the Tool or Adapt the Model of Our Arm?

Abstract: We make errors when learning to use a new tool. However, the cause of error may be ambiguous: is it because we misestimated properties of the tool or of our own arm? We considered a well-studied adaptation task in which people made goal-directed reaching movements while holding the handle of a robotic arm. The robot produced viscous forces that perturbed reach trajectories. As reaching improved with practice, did people recalibrate an internal model of their arm, or did they build an internal model of the novel tool (robot), or both? What factors influenced how the brain solved this credit assignment problem? To investigate these questions, we compared transfer of adaptation between three conditions: catch trials in which robot forces were turned off unannounced, robot-null trials in which subjects were told that forces were turned off, and free-space trials in which subjects still held the handle but watched as it was detached from the robot. Transfer to free space was 40% of that observed in unannounced catch trials. We next hypothesized that transfer to free space might increase if the training field changed gradually, rather than abruptly. Indeed, this method increased transfer to free space from 40 to 60%. Therefore although practice with a novel tool resulted in formation of an internal model of the tool, it also appeared to produce a transient change in the internal model of the subject's arm. Gradual changes in the tool's dynamics increased the extent to which the nervous system recalibrated the model of the subject's own arm.

Runtime software adaptation: framework, approaches, and styles

Abstract: Our ICSE 1998 paper showed how an application can be adapted at runtime by manipulating its architectural model. In particular, our paper demonstrated the beneficial role of (1) software connectors in aiding runtime change, (2) an explicit architectural model fielded with the system and used as the basis for runtime change, and (3) architectural style in providing both structural and behavioral constraints over runtime change. This paper examines runtime evolution in the decade hence. A broad framework for studying and describing evolution is introduced that serves to unify the wide range of work now found in the field of dynamic software adaptation. This paper also looks to the future, identifying what we believe to be highly promising directions.

Internal Regulatory Variables and the Design of Human Motivation: A Computational and Evolutionary Approach

Abstract: Internal regulatory variables and the design of human motivation: A computational and evolutionary approach. Cognitive psychology and evolutionary biology both offer compelling visions of what the brain does, but there is a radical disconnect between them. Evolutionary biology tells us that we are beings whose brains evolved to pursue utilitarian goals, goals that promoted survival and reproduction in ancestral environments. Cognitive psychology tells us that our brains contain mechanisms of perception, 250 Handbook of Approach and Avoidance Motivation attention, memory, reasoning, and learning that, while not infallible, produce knowledge that tracks at least some aspects of reality. Fodor goes even further: he says that the function of cognition is " the fi xation of true beliefs " (Fodor, 2000, p. 68). This sounds fi ne, until you realize the problem. True beliefs, by themselves, contain no information about how to behave—what to value, what to approach, what to avoid. Encyclopedias have no motivations. Value is not a property of the world, there to be discovered. Dung is not disgusting—it is disgusting to us, but attractive to dung fl ies. A man may be sexually attractive to many women, but sexually repulsive to his sister. Like beauty, value is in the adaptations of the beholder (Symons, 1995). The question we have been addressing in our research is how to incorporate the study of value and motivation into the framework of the cognitive sciences. There have been two strands to these explorations. The fi rst involves reasoning and concepts; the second is a new way of thinking about motivation that is both computational and grounded in evolutionary biology. A common view in cognitive psychology, most forcefully articulated by Fodor (2000), is that reasoning and concepts are designed for acquiring true beliefs, so their study can be walled off from the study of motivation—from so-called conative mechanisms, governing preferences, approach, and avoidance. In direct contrast to this view, our earliest research on reasoning was motivated by results from evolutionary game theory, which models conative (i.e., behavior-producing) mechanisms. Agents endowed with different behavior-producing mechanisms are allowed to interact, and the payoffs of these interactions determine how many copies of each (mechanism-bearing) agent appear in the next generation. This simulates how natural selection works, allowing one to see which mechanism types, which designs, will be retained over time and which will be eliminated from the population. One can then test to see whether mechanisms with …

A MCDM-based expert system for climate-change impact assessment and adaptation planning - A case study for the Georgia Basin, Canada

Abstract: An MCDM-based expert system was developed to tackle the interrelationships between the climate change and the adaptation policies in terms of water resources management in the Georgia Basin, Canada User interfaces of the developed expert system, named MAEAC (MCDM-based expert system for adaptation analysis under changing climate), was developed based on system configuration, knowledge acquisition, survey analysis, and MCDM-based policy analysis A number of processes that were vulnerable to climate change were examined and pre-screened through extensive literature review, expert consultation and statistical analysis Adaptation policies to impacts of temperature increase, precipitation-pattern variation and sea-level rise were comprehensively explicated and incorporated within the developed system The MAEAC could be used for both acquiring knowledge of climate-change impacts on water resources in the Georgia Basin and supporting formulation of the relevant adaptation policies It can also be applied to other watersheds to facilitate assessment of climate-change impacts on socio-economic and environmental sectors, as well as formulation of relevant adaptation policies

Goal-Based Modeling of Dynamically Adaptive System Requirements

Abstract: Self-adaptation is emerging as an increasingly important capability for many applications, particularly those deployed in dynamically changing environments, such as ecosystem monitoring and disaster management. One key challenge posed by dynamically adaptive systems (DASs) is the need to handle changes to the requirements and corresponding behavior of a DAS in response to varying environmental conditions. Berry et al. previously identified four levels of RE that should be performed for a DAS. In this paper, we propose the levels of RE for modeling that reify the original levels to describe RE modeling work done by DAS developers. Specifically, we identify four types of developers: the system developer, the adaptation scenario developer, the adaptation infrastructure developer, and the DAS research community. Each level corresponds to the work of a different type of developer to construct goal model(s) specifying their requirements. We then leverage the levels of RE for modeling to propose two complementary processes for performing RE for a DAS. We describe our experiences with applying this approach to GridStix, an adaptive flood warning system, deployed to monitor the River Ribble in Yorkshire, England.

Using Planned Adaptation to Implement Evidence‐Based Programs with New Populations

Abstract: The Interactive Systems Framework (ISF) for Dissemination and Implementation (Wandersman et al. 2008) elaborates the functions and structures that move evidence-based programs (EBPs) from research to practice. Inherent in that process is the tension between implementing programs with fidelity and the need to tailor programs to fit the target population. We propose Planned Adaptation as one approach to resolve this tension, with the goal of guiding practitioners in adapting EBPs so that they maintain core components of program theory while taking into account the needs of particular populations. Planned Adaptation is a form of capacity building within the Prevention Support System that provides a framework to guide practitioners in adapting programs while encouraging researchers to provide information relevant to adaptation as a critical aspect of dissemination research, with the goal of promoting wider dissemination and better implementation of EBPs. We illustrate Planned Adaptation using the JOBS Program (Caplan et al. 1989), which was developed for recently laid-off, working- and middle-class workers and subsequently implemented with welfare recipients.

Model-Based Adaptation of Behavioral Mismatching Components

Abstract: Component-Based Software Engineering focuses on the reuse of existing software components. In practice, most components cannot be integrated directly into an application-to-be, because they are incompatible. Software Adaptation aims at generating, as automatically as possible, adaptors to compensate mismatch between component interfaces, and is therefore a promising solution for the development of a real market of components promoting software reuse. In this article, we present our approach for software adaptation which relies on an abstract notation based on synchronous vectors and transition systems for governing adaptation rules. Our proposal is supported by dedicated algorithms that generate automatically adaptor protocols. These algorithms have been implemented in a tool, called Adaptor, that can be used through a user-friendly graphical interface.

A capabilities-based model for adaptive organizations

Abstract: Multiagent systems have become popular over the last few years for building complex, adaptive systems in a distributed, heterogeneous setting. Multiagent systems tend to be more robust and, in many cases, more efficient than single monolithic applications. However, unpredictable application environments make multiagent systems susceptible to individual failures that can significantly reduce its ability to accomplish its overall goal. The problem is that multiagent systems are typically designed to work within a limited set of configurations. Even when the system possesses the resources and computational power to accomplish its goal, it may be constrained by its own structure and knowledge of its member's capabilities. To overcome these problems, we are developing a framework that allows the system to design its own organization at runtime. This paper presents a key component of that framework, a metamodel for multiagent organizations named the Organization Model for Adaptive Computational Systems. This model defines the requisite knowledge of a system's organizational structure and capabilities that will allow it to reorganize at runtime and enable it to achieve its goals effectively in the face of a changing environment and its agent's capabilities.

Team learning, development, and adaptation

Abstract: [Excerpt] Our purpose is to explore conceptually these themes centered on team learning, development, and adaptation. We note at the onset that this chapter is not a comprehensive review of the literature. Indeed, solid conceptual and empirical work on these themes are sparse relative to the vast amount of work on team effectiveness more generally, and therefore a thematic set of topics that are ripe for conceptual development and integration. We draw on an ongoing stream of theory development and research in these areas to integrate and sculpt a distinct perspective on team learning, development, and adaptation.

Predictability and accuracy in adaptive user interfaces

Abstract: While proponents of adaptive user interfaces tout potential performance gains, critics argue that adaptation's unpredictability may disorient users, causing more harm than good. We present a study that examines the relative effects of predictability and accuracy on the usability of adaptive UIs. Our results show that increasing predictability and accuracy led to strongly improved satisfaction. Increasing accuracy also resulted in improved performance and higher utilization of the adaptive interface. Contrary to our expectations, improvement in accuracy had a stronger effect on performance, utilization and some satisfaction ratings than the improvement in predictability.

The psychology of tailoring-ingredients of computer-tailored persuasion.

Abstract: Persuasive information can be tailored to individual characteristics using computer technology. Computer technology offers three ways to persuade people: adaptation, personalization, and feedback. Adaptation refers to the match between the type or the formulation of the persuasive arguments or recommendations and an individual's psychological state. Personalization refers to the incorporation of one or more recognizable individual characteristics (e.g., one's first name) in a persuasive text. Feedback refers to providing the individual with information about him or her that relates to important individual goals. These visible elements in a persuasive message are the tailoring-ingredients of computer-tailored persuasion. The present article focuses on explaining how these tailoring-ingredients influence persuasion, using existing social psychological insights in human functioning and persuasion. The persuasive effects of the tailoring-ingredients can be explained partly by different psychological processes. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

Individual Adaptation to IT-Induced Change: The Role of Social Networks

Abstract: In order to better understand the sociopsychological factors involved in employees' adaptation to new technology in organizations, we examine the role that two types of social networks-supportive and informational-play in individual adaptation to IT-induced change in a large financial company. Using survey data from 371 employees working in 133 different branches of the organization, we find that several aspects of the social networks relate to quality of employees' adaptation to the new technology as assessed by the company's departmental directors. Specifically, the size of the support network as well as the strength and density of the information network significantly predict employees' adaptation to the new system. We conclude the paper by discussing theoretical implications for the relevance of social network research for members' adaptation to organizational changes as well as outlining specific implications for practice.

Spell-check for a keyboard system with automatic correction

Abstract: An adaptation of standard edit distance spell-check algorithms leverages probability-based regional auto-correction algorithms and data structures for ambiguous keypads and other predictive text input systems to provide enhanced typing correction and spell-check features. Strategies for optimization and for ordering results of different types are also provided.

Rainbow: cost-effective software architecture-based self-adaptation

Abstract: Modern, complex software systems (e-commerce, IT, critical infrastructures, etc.) are increasingly required to continue operation in the face of change, to self-adapt to accommodate shifting user priorities, resource variability, changing environments, and component failures. While manual oversight benefits from global problem contexts and flexible policies, human operators are costly and prone to error. Low-level, embedded mechanisms (exceptions, time-outs, etc.) are effective and timely for error recovery, but are local in scope to the point-of-failure, application-specific, and costly to modify when adaptation objectives change. An ideal solution leverages domain expertise, provides an end-to-end system perspective, adapts the system in a timely manner, and can be engineered cost-effectively. Architecture-based self-adaptation closes the “loop of control,” using external mechanisms and the architecture model of the target system to adapt the system. An architecture model exposes important system properties and constraints, provides end-to-end problem contexts, and allows principled and automated adaptations. Existing architecture-based approaches specialize support for particular classes of systems and fixed sets of quality-of-service concerns; they are costly to develop for new systems and to evolve for new qualities. To overcome these limitations, we posit this thesis: We can provide software engineers the ability to add and evolve self-adaptation capabilities cost-effectively, for a wide range of software systems, and for multiple objectives, by defining a self-adaptation framework that factors out common adaptation mechanisms and provides explicit customization points to tailor self-adaptation capabilities for particular classes of systems, for multiple quality-of-service objectives. Our approach, embodied in a system called Rainbow, provides an engineering approach and a framework of mechanisms to monitor a target system and its environment, reflect observations into the system's architecture model, detect opportunities for improvements, select a course of action, and effect changes. The framework provides general and reusable infrastructures with well-defined customization points, a set of abstractions, and an adaptation engineering process, focusing engineers on adaptation concerns to systematically customize Rainbow to particular systems. To automate system self-adaptation, Rainbow provides a language, called Stitch, to represent routine human adaptation knowledge using a core set of adaptation concepts.

Using cognitive principles to guide classification in information systems modeling

Abstract: Organizing phenomena into classes is a pervasive human activity. The ability to classify phenomena encountered in daily life in useful ways is essential to human survival and adaptation. Not surprisingly, then, classification-oriented activities are widespread in the information systems field. Classes or entity types play a central role in conceptual modeling for information systems requirements analysis, as well as in the design of databases and object-oriented software. Furthermore, classification is the primary task in applications such as data mining and the development of domain ontologies to support information sharing in semantic web applications. However, despite the pervasiveness of classification, little research has proposed well-grounded guidelines for identifying, evaluating, and choosing classes when modeling a domain or designing information systems artifacts. In this paper, we adopt the cognitive notions of inference and economy to derive a set of principles to guide effective and efficient classification. We present a model for characterizing what may be considered useful classes in a given context based on the inferences that can be drawn from membership in a class. This foundation is then used to suggest practical design rules for evaluating and refining potential classes. We illustrate the use of the rules by showing that applying them to a previously published example yields meaningful changes. We then present an evaluation by a panel of experts who compared the published and revised models. The evaluation shows that following the rules leads to semantically clearer models that are preferred by experts. The paper concludes by outlining possible future research directions.

Affective feedback: an investigation into the role of emotions in the information seeking process

Abstract: User feedback is considered to be a critical element in the information seeking process. An important aspect of the feedback cycle is relevance assessment that has progressively become a popular practice in web searching activities and interactive information retrieval (IR). The value of relevance assessment lies in the disambiguation of the user's information need, which is achieved by applying various feedback techniques. Such techniques vary from explicit to implicit and help determine the relevance of the retrieved documents.The former type of feedback is usually obtained through the explicit and intended indication of documents as relevant (positive feedback) or irrelevant (negative feedback). Explicit feedback is a robust method for improving a system's overall retrieval performance and producing better query reformulations [1], at the expense of users' cognitive resources. On the other hand, implicit feedback techniques tend to collect information on search behavior in a more intelligent and unobtrusive manner. By doing so, they disengage the users from the cognitive burden of document rating and relevance judgments. Information-seeking activities such as reading time, saving, printing, selecting and referencing have been all treated as indicators of relevance, despite the lack of sufficient evidence to support their effectiveness [2].Besides their apparent differences, both categories of feedback techniques determine document relevance with respect to the cognitive and situational levels of the interactive dialogue that occurs between the user and the retrieval system [5]. However, this approach does not account for the dynamic interplay and adaptation that takes place between the different dialogue levels, but most importantly it does not consider the affective dimension of interaction. Users interact with intentions, motivations and feelings apart from real-life problems and information objects, which are all critical aspects of cognition and decision-making [3][4]. By evaluating users' affective response towards an information object (e.g. a document), prior and post to their exposure to it, a more accurate understanding of the object's properties and degree of relevance to the current information need may be facilitated. Furthermore, systems that can detect and respond accordingly to user emotions could potentially improve the naturalness of human-computer interaction and progressively optimize their retrieval strategy. The current study investigates the role of emotions in the information seeking process, as the latter are communicated through multi-modal interaction, and reconsiders relevance feedback with respect to what occurs on the affective level of interaction as well.

An Aspect-Oriented and Model-Driven Approach for Managing Dynamic Variability

Abstract: Constructing and executing distributed systems that can adapt to their operating context in order to sustain provided services and the service qualities are complex tasks. Managing adaptation of multiple, interacting services is particularly difficult since these services tend to be distributed across the system, interdependent and sometimes tangled with other services. Furthermore, the exponential growth of the number of potential system configurations derived from the variabilities of each service need to be handled. Current practices of writing low-level reconfiguration scripts as part of the system code to handle run time adaptation are both error prone and time consuming and make adaptive systems difficult to validate and evolve. In this paper, we propose to combine model driven and aspect oriented techniques to better cope with the complexities of adaptive systems construction and execution, and to handle the problem of exponential growth of the number of possible configurations. Combining these techniques allows us to use high level domain abstractions, simplify the representation of variants and limit the problem pertaining to the combinatorial explosion of possible configurations. In our approach we also use models at runtime to generate the adaptation logic by comparing the current configuration of the system to a composed model representing the configuration we want to reach.

RouteCheckr: personalized multicriteria routing for mobility impaired pedestrians

Abstract: Mobility impaired people use a variety of assistive technologies to navigate independently in everyday life. Although several technical approaches for navigation systems exist, many drawbacks remain due to lack of geospatial resolution, inadequate geographical data provided, and missing adaptation of routes to a multitude of user specific criteria. We developed RouteCheckr, a client/server system for collaborative multimodal annotation of geographical data and personalized routing of mobility impaired pedestrians. The construction of algorithms supporting multiple bipolar criteria is described, applied to route calculation, and demonstrated in our university's campus. To satisfy individual requirements, user profiles are incorporated enabling adaptivity over heterogeneous user groups while preserving privacy. Finally, a general architecture for RouteCheckr is presented and simulation results are analyzed.

Visibility of control in adaptive systems

Abstract: Adaptive systems respond to changes in their internal state or external environment with guidance from an underlying control system. ULS systems are particularly likely to require dynamic adaptation because of their decentralized control and the large number of independent stakeholders whose actions are integral to the system's behavior. Adaptation may take various forms, but the system structure will almost inevitably include one or more closed feedback loops. We argue that adaptability is a characteristic of a solution, not of a problem, and that the feedback loop governing control of adaptability should be explicit in design and analysis and either explicit or clearly traceable in implementation.