Global adaptation in networks of selfish components: emergent associative memory at the system scale

In some circumstances complex adaptive systems composed of numerous self-interested agents can self-organise into structures that enhance global adaptation, efficiency or function. However, the general conditions for such an outcome are poorly understood and present a fundamental open question for domains as varied as ecology, sociology, economics, organismic biology and technological infrastructure design. In contrast, sufficient conditions for artificial neural networks to form structures that perform collective computational processes such as associative memory/recall, classification, generalisation and optimisation, are well-understood. Such global functions within a single agent or organism are not wholly surprising since the mechanisms (e.g. Hebbian learning) that create these neural organisations may be selected for this purpose, but agents in a multi-agent system have no obvious reason to adhere to such a structuring protocol or produce such global behaviours when acting from individual self-interest. However, Hebbian learning is actually a very simple and fully-distributed habituation or positive feedback principle. Here we show that when self-interested agents can modify how they are affected by other agents (e.g. when they can influence which other agents they interact with) then, in adapting these inter-agent relationships to maximise their own utility, they will necessarily alter them in a manner homologous with Hebbian learning. Multi-agent systems with adaptable relationships will thereby exhibit the same system-level behaviours as neural networks under Hebbian learning. For example, improved global efficiency in multi-agent systems can be explained by the inherent ability of associative memory to generalise by idealising stored patterns and/or creating new combinations of sub-patterns. Thus distributed multi-agent systems can spontaneously exhibit adaptive global behaviours in the same sense, and by the same mechanism, as the organisational principles familiar in connectionist models of organismic learning

Understanding adaptability through layer dependencies

This paper looks at change from the perspective of building design (i.e. building adaptability), and how a better understanding of product architecture can bring about an easier accommodation of change for an unforeseeable future. The work explores the use of a design structure matrix (DSM) to understand the building's capacity to accommodate change using building decomposition methods (Brand's layers) and component interactions as initial guides to suggest possible product architectures. Research for this study took place along side the design stage of an ongoing BSF school project. The systematic analysis of design drawings and reports was undertaken in three phases: code documents using Brand's layers; identify all variant components to create a work breakdown structure; and classification of all component relationships populating a DSM. Simple principles, such as achieving modularity between component dependencies, can potentially reveal the implication of changing components. Insights that have been gained through the data include the appropriate layer placement of components, the possibilities of new/different layers, and the highlighting of unwanted/ hidden dependencies. The DSM permutations have also provided a deeper understanding of the software used and its algorithmic behavior, giving greater clarity of the organization of the components, and the development of component typologies in an effort to provide a consistent, logical approach to refining the matrix

Organizational Pressures Driving the Growth of Contingent Faculty

Organizational pressures influence the restructuring of the academic workforce. This chapter describes the key factors associated with increased hiring of contingent faculty.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142975/1/ir20242.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142975/2/ir20242_am.pd

A conceptual system design and managerial complexity competency model

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Complex adaptive systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex adaptive systems. The challenges of designing complex adaptive systems in a highly dynamic world drive the need for anticipatory capacity within engineering organizations, with a goal of enabling the design of systems that can cope with an unpredictable environment. This thesis explores this question of enhancing anticipatory capacity through the study of a complex adaptive system design methodology and complexity management competencies. A general introduction to challenges and issues in complex adaptive systems design is given, since a good understanding of the industrial context is considered necessary in order to avoid oversimplification of the problem, neglecting certain important factors and being unaware of important influences and relationships. In addition, a general introduction to complex thinking is given, since designing complex adaptive systems requires a non-classical thought, while practical notions of complexity theory and design are put forward. Building on these, the research proposes a Complex Systems Life-Cycle Understanding and Design (CXLUD) methodology to aid system architects and engineers in the design and control of complex adaptive systems. Starting from a creative anticipation construct - a loosening mechanism to allow for more options to be considered, the methodology proposes a conceptual framework and a series of stages to follow to find proper mechanisms that will promote elements to desired solutions by actively interacting among themselves. To illustrate the methodology, a financial systemic risks infrastructure systems architecture development case study is presented. The final part of this thesis develops a conceptual model to analyse managerial complexity competency model from a qualitative phenomenological study perspective. The model developed in this research is called Understanding-Perception-Action (UPA) managerial complexity competency model. The results of this competency model can be used to help ease project manager’s transition into complex adaptive projects, as well as serve as a foundation to launch qualitative and quantitative research into this area of project complexity management

Government as a platform, orchestration, and public value creation: the Italian case

E-Government literature has discussed how the adoption of the Government as a Platform (GaaP) can help public administration to produce more efficient public services. However, since little attention has been given to the impact of GaaP on public value creation more research is needed to analyse whether the GaaP is effective to help the government to deliver public services that fulfil social expectations and, hence, public value. Indeed, effi-ciency does not guarantee public value. Besides efficiency, public value incorporates citizens' variegated ex-pectations and needs that change over time and that are sometimes rival. For these reasons, the delivery of public value is often challenging for public agencies. The aim of this paper is to explain how the GaaP config-uration can help public administration to deliver public value better. The paper finds that the modularity of the platform configuration and different ecosystems that support public agencies need to be orchestrated to support the effective creation of public value. The authors analyse the case of the Italian GaaP initiative to discuss the importance of the orchestration of the GaaP characteristics to improve the coordination among public agencies and enable the co-production of services with external actors, in order to deliver public value better. The findings show that the orchestration of the GaaP configuration characteristics can enable Italian public administration to deliver public value, but also that, if the GaaP is not properly orchestrated, it can constrain the creation of public value

100 Years of Training and Development Research: What We Know and Where We Should Go

Training and development research has a long tradition within applied psychology dating back to the early 1900’s. Over the years, not only has interest in the topic grown but there have been dramatic changes in both the science and practice of training and development. In the current article, we examine the evolution of training and development research using articles published in the Journal of Applied Psychology (JAP) as a primary lens to analyze what we have learned and to identify where future research is needed. We begin by reviewing the timeline of training and development research in JAP from 1918 to the present in order to elucidate the critical trends and advances that define each decade. These trends include the emergence of more theory-driven training research, greater consideration of the role of the trainee and training context, examination of learning that occurs outside the classroom, and understanding training’s impact across different levels of analysis. We then examine in greater detail the evolution of four key research themes: training criteria, trainee characteristics, training design and delivery, and the training context. In each area, we describe how the focus of research has shifted over time and highlight important developments. We conclude by offering several ideas for future training and development research

Designing for adaptability in architecture

The research is framed on the premise that designing buildings that can adapt by accommodating change easier and more cost-effectively provides an effective means to a desired end a more sustainable built environment. In this context, adaptability can be viewed as a means to decrease the amount of new construction (reduce), (re)activate underused or vacant building stock (reuse) and enhance disassembly/ deconstruction of components (reuse, recycle) - prolonging the useful life of buildings (reduce, reuse, recycle). The aim of the research is to gain a holistic overview of the concept of adaptability in the construction industry and provide an improved framework to design for, deploy and implement adaptability. An over-arching research question was posited to guide the inquiry: how can architects understand, communicate, design for and test the concept of adaptability in the context of the design process? The research followed Dubois and Gadde s (2002) systematic combining as an over-arching approach that continuously moves between the empirical world and theoretical models allowing the co-evolution of data collection and theory from the beginning as part of a non-linear process with the objective of matching theory with reality. An initial framework was abducted from a preliminary collection of data from which a set of mixed research methods was deployed to explore adaptability (interviews, building case studies, dependency structural matrices, practitioner surveys and workshop). Emergent from the data is an expanded and revised theory on designing for adaptability consisting of concepts, models and propositions. The models illustrate many of the casual links between the physical design structure of the building (e.g. plan depth, storey height) and the soft contingencies of a messy design/construction/occupation process (e.g. procurement route, funding methods, stakeholder mindsets). In an effort to enhance building adaptability, the abducted propositions suggest a shift in the way the industry values buildings and conducts aspects of the design process and how designer s approach designing for adaptability