A General Theory of Emergence in Engineered Systems

Engineered systems are designed to satisfy specific needs and produce explainable/predictable results. But despite this intent, engineered systems don’t always do what they are designed to do once they are implemented. Some engineered systems produce properties and behaviors that are not clearly explainable or predictable by the properties of their components. This is a problem recognized in government and private sectors as having broad ranging financial and security consequences. It is also the essence of the emergence phenomena. A review of the literature reveals two significant gaps in the current body of knowledge on emergence as it pertains to engineered systems: 1) no conceptual model that reconciles conflicting aspects of emergence; and 2) no explanation of system factors and their relationships that affect the occurrence of emergence. The gaps are addressed in this dissertation through research using a methodology that incorporates rationalist inductive methods with modeling & simulation frameworks. Where other research and models of emergence focus on entity or agent behavior; the research in this dissertation takes place from a systems perspective. The focus is on system level behaviors and system factors as they pertain to the occurrence of emergent effects. Generally accepted thermodynamic principles and axioms for chemical reactions are used to develop scientific analogies for factors in engineered systems. A theory is derived consisting of six factors that are determinants in a mathematical model of a tipping point at which emergent effects will occur in engineered systems: 1) interoperability; 2) concentration of components; 3) component degrees of freedom; 4) variety of system regulators; 5) rate of information received vs transmitted by the system; and 6) relative amount of information received by the system vs a threshold for change in the system configuration. The theory and its implications are explored in simulation experiments. Other products and contributions of the research include: a) an ontology of emergence concepts; b) a unifying definition of emergence; and c) a system dynamics model of emergence in engineered systems

Knowledge transfer in cognitive systems theory: models, computation, and explanation

Knowledge transfer in cognitive systems can be explicated in terms of structure mapping and control. The structure of an effective model enables adaptive control for the system's intended domain of application. Knowledge is transferred by a system when control of a new domain is enabled by mapping the structure of a previously effective model. I advocate for a model-based view of computation which recognizes effective structure mapping at a low level. Artificial neural network systems are furthermore viewed as model-based, where effective models are learned through feedback. Thus, many of the most popular artificial neural network systems are best understood in light of the cybernetic tradition as error-controlled regulators. Knowledge transfer with pre-trained networks (transfer learning) can, when automated like other machine learning methods, be seen as an advancement towards artificial general intelligence. I argue this is convincing because it is akin to automating a general systems methodology of knowledge transfer in scientific reasoning. Analogical reasoning is typical in such a methodology, and some accounts view analogical cognition as the core of cognition which provides adaptive benefits through efficient knowledge transfer. I then discuss one modern example of analogical reasoning in physics, and how an extended Bayesian view might model confirmation given a structural mapping between two systems. In light of my account of knowledge transfer, I finally assess the case of quantum-like models in cognition, and whether the transfer of quantum principles is appropriate. I conclude by throwing my support behind a general systems philosophy of science framework which emphasizes the importance of structure, and which rejects a controversial view of scientific explanation in favor of a view of explanation as enabling control

Exploring the Lived-Experience of business model innovation

Due to increasingly complex and uncertain environments, businesses must deal with multiple competing and often opposing models, what we may call 'ontological relativity'. To deal with this, the practice of innovation management requires a new type of practical-epistemology. The best insight into these new types of knowledge is an exploration of lived experience of innovation management practitioners. This research then explores the phenomena involved in the practice of business model innovation in the context of two innovation projects. To achieve these goals, a phenomenological method is used to uncover fundamental aspects of the innovation process. The outcome of the inquiry is a set a set of phenomena that hope to contribute to the discourse around this emerging field of management knowledge

Analogical creative thinking and its application to engineering design and enterprise

Analogical thinking is valuable to creative design as it assists generation of new knowledge by mapping analogically from source domain to target domain. This study endeavours to enhance the value of analogical thinking in creative design by the development of Analogical Creative Process (ACP), and evaluation of its application in projects of engineering design and enterprise design. ACP is a systematic step-by-step tool to enable analogical thinking in design, and is derived from the fundamental cognitive process of key theories for analogy establishment. It analyses the given design problem as a complex of sub-systems and identifies their functions, before analogically mapping over the relations among the sub-systems between different domains. With these features, ACP is capable of providing tangible guidance on analogical thinking for designers without requirement of their existing experience in use of analogy. The effectiveness of ACP in creative ideation is examined with positive outcome observed in a real-life engineering design project compared to non-analogical approaches. The interrelations between creativity, analogy and design are identified featuring ACP and analogical thinking through a prescriptive study. As a result, a novel analogy-empowered creative design process is proposed and applied in an enterprise design project as a new field of application for analogical thinking in design. Initial evaluation supports the application success of the creative design process and analogical thinking is proven valuable in assisting enterprise design practices. The outcomes of this study include development of ACP based on the cognitive model of analogy, establishment of a new connection between creativity, analogy and design by the analogy-embedded creative design process, and a new design application of analogical thinking in enterprise. The identification of the value of analogical thinking in the context of enterprise design provides the researchers and entrepreneurs with a new tool to enhance enterprise design and business progress.Open Acces

Proceedings of the 18th Irish Conference on Artificial Intelligence and Cognitive Science

These proceedings contain the papers that were accepted for publication at AICS-2007, the 18th Annual Conference on Artificial Intelligence and Cognitive Science, which was held in the Technological University Dublin; Dublin, Ireland; on the 29th to the 31st August 2007. AICS is the annual conference of the Artificial Intelligence Association of Ireland (AIAI)

Analogies in Physics

This thesis investigates what tools are appropriate for answering the question how it is possible to develop such a complex theory in physics as the standard model of particle physics with only an access via electromagnetic interaction of otherwise unobservable objects and their interactions it was investigated what the tools are to do this. The answer is found in the usage of essentially two types of analogies. These two types are explanatory and predictive analogies. Explanatory analogies are needed to link observed new phenomena to accepted scientific theoretical models of well-known phenomena, predictive analogies to find in possible experiments further new phenomena not already observed. The possibilities of observation and the related conditions are the main reason to use analogies as well in the development of theories, as in the representation of experiments especially in high energy physics, because there we find only charged particles observable via electromagnetic interaction. Other neutral particles with no charge are concludable only by visualization of their assumed tracks filling the gaps between the tracks of charged and therefore in some way observable particles. Today this is only possible with the help of computers evaluating the huge amount of data delivered by extremely complex detectors using the electromagnetic interaction in different ways. This visualization is also a kind of analogy because in fact all the particles are not observable directly, only their electromagnetic interaction if it occurs. My investigation considered reasons for the following questions: Why in philosophy of science analogies were neglected during about one hundred years? How can analogies be characterized? And at last, as point of origination for my investigation where have analogies played an important role the development of high energy physics from the explanation of the constitution of the atomic core to the postulation of quarks, mainly in original publications? Important in this task is especially the consideration of the context which determines in some way the possible directions of development, however, no direction of development in general. The intention in my thesis was to shed some more light on the epistemological side of scientific work in physics and how analogies could help enabling this task. The method used was primarily text analysis of mostly original publications of leading physicists

From primitives to primates

Where do our images about early hominids come from? In this fascinating in-depth study, David Van Reybrouck demonstrates how input from ethnography and primatology has deeply influenced our visions about the past from the 19th century to this day – often far beyond the available evidence. Victorian scholars were keen to look at contemporary Australian and Tasmanian aboriginals to understand the enigmatic Neanderthal fossils. Likewise, today’s primatologists debate to what extent bonobos, baboons or chimps may be regarded as stand-ins for early human ancestors. The belief that the contemporary world provides ‘living links’ still goes strong. Such primate models, Van Reybrouck argues, continue the highly problematic ‘comparative method’ of the Victorian times. He goes on to show how the field of ethnoarchaeology has succeeded in circumventing the major pitfalls of such analogical reasoning. A truly interdisciplinary study, this work shows how scholars working in different fields can effectively improve their methods for interpreting the deep past by understanding the historical challenges of adjacent disciplines. Overviewing two centuries of intellectual debate in fields as diverse as archaeology, ethnography and primatology, Van Reybrouck’s book is one long plea for trying to understand the past on its own terms, rather than as facile projections from the present. David Van Reybrouck (Bruges, 1971) was trained as an archaeologist at the universities of Leuven, Cambridge and Leiden. Before becoming a highly successful literary author (The Plague, Mission, Congo…), he worked as a historian of ideas. For more than twelve years, he was coeditor of Archaeological Dialogues. In 2011-12, he held the prestigious Cleveringa Chair at the University of Leiden

Gaining Insight into Determinants of Physical Activity using Bayesian Network Learning

Contains fulltext : 228326pre.pdf (preprint version ) (Open Access) Contains fulltext : 228326pub.pdf (publisher's version ) (Open Access)BNAIC/BeneLearn 202