27,976 research outputs found

    A Process Approach to Corporate Coherence

    Get PDF
    We address the notion of 'corporate coherence', recently made prominent by Teece, Rumelt, Dosi and Winter (1994). We argue that the literature is confused on the meaning of the notion (and similar notions) in a number of dimensions. Drawing on insights from market-process theories, we put forward a dynamic understanding of corporate coherence as involving the corporate capacity to strike a favorable balance between the production and the exploitation of new knowledge. This argument is elaborated drawing on Austrian, evolutionary and post- Marshallian economics.Corporate coherence, knowledge, competences

    Big data analytics:Computational intelligence techniques and application areas

    Get PDF
    Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

    Robotic ubiquitous cognitive ecology for smart homes

    Get PDF
    Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

    A Survey on Natural Inspired Computing (NIC): Algorithms and Challenges

    Get PDF
    Nature employs interactive images to incorporate end users2019; awareness and implication aptitude form inspirations into statistical/algorithmic information investigation procedures. Nature-inspired Computing (NIC) is an energetic research exploration field that has appliances in various areas, like as optimization, computational intelligence, evolutionary computation, multi-objective optimization, data mining, resource management, robotics, transportation and vehicle routing. The promising playing field of NIC focal point on managing substantial, assorted and self-motivated dimensions of information all the way through the incorporation of individual opinion by means of inspiration as well as communication methods in the study practices. In addition, it is the permutation of correlated study parts together with Bio-inspired computing, Artificial Intelligence and Machine learning that revolves efficient diagnostics interested in a competent pasture of study. This article intend at given that a summary of Nature-inspired Computing, its capacity and concepts and particulars the most significant scientific study algorithms in the field

    Enhancing Innovation Through Biologically Inspired Design

    Get PDF
    Mixing upper level undergraduates majoring in engineering with those majoring in biology, we have devised a course on biologically-inspired design (BID) that provides practical training in methods and techniques that facilitate the identification and translation of biological principles into solutions for human challenges. The challenges of interdisciplinary courses generally, and the specific challenges of fostering exchange among biologists and engineers lead us to define these learning goals: (1) basic knowledge of successful examples of BID, (2) interdisciplinary communication skills, (3) knowledge about domains outside of their core training, (4) a uniquely interdisciplinary design process, and (5) how to apply existing technical knowledge to a new discipline. We developed the following course components to meet the key learning objectives: BID Lectures; Design Lectures; Found object exercises; Quantitative assessments; Analogy exercises; Research assignments; Interdisciplinary Collaboration, Mentorship; Idea Journals and Reflections. We will provide an extensive description of these elements, which we have chosen to incorporate based on our own experience with interdisciplinary communication, as well as findings from cognitive science regarding how students actually learn. This 15 week course is organized using assignments of increasing complexity that allow students to learn and apply essential skills of BID methodology and practice. Early exercises, which combine lectures, group discussions and individual assignments, have these objectives: 1) allow students to develop the necessary inter-disciplinary communication and research skills to facilitate their design project work; 2) expose students to ideation and design skills that will encourage them to work outside of their comfort zone; 3) practice the analogical reasoning skills that facilitate the successful search for and application of relevant biological concepts. This initial portion of the course stresses that BID occurs at the early phase of a design process and that identifying solutions from the biological domain requires that students have a sufficient breakdown of their problem combined with sufficient biological knowledge to suggest appropriate mappings between problem and solution. Two primary barriers are a lack of appreciation for how the evolutionary “design” process differs from human design, and the use of different terminology for describing similar processes in biology vs. engineering. We describe some teaching practices and activities that allow students to overcome these difficulties. The course culminates in a group project, which is a detailed conceptual design including a preliminary analysis of expected performance, value, and feasibility. A unique feature of the course is that it represents the efforts of not only biologists and engineers, but also contributions from cognitive scientists engaged in understanding human cognition and creativity. Our course strategy has been deeply influenced by findings in that field. We have studied the activity of classroom participants for the last three years, examining the processes they use, and intermediate and final design representations. Analysis of this has yielded a number of observations about the cognitive process of biologically inspired design that may provide insights regarding how to enhance BID education, as well as provide useful insight for professionals in the design field. Key words: biologically-inspired design (BID); interdisciplinary communicatio

    The two social philosophies of Ostroms' institutionalism

    Get PDF
    The article argues that Ostroms’ institutionalism has a dimension that is complex and profound enough to deserve to be considered a “social theory” or a “social philosophy”. The paper pivots around the thesis that the “social philosophy” behind the Bloomington School’s research agenda has in fact two facets that may or may not be consistent with each other. The article describes the main features of the two facets, offers a brief overview of the development of these ideas, and clarifies their relationship to Public Choice theory and alternative visions of public goods analysis, public administration, and governance. The argument goes further to raise the provocative question whether the two “social philosophies” involved in the approach undertaken by Elinor Ostrom and Vincent Ostrom are necessarily and inseparably connected with the rest of their research program.Institutional Theory; Polycentricity; Governance; Public choice; Institutional Design; Social Theory
    corecore