This resource motivates and develops a new research programme in epistemology that is centred around the concept of epistemic autonomy.--

Autonomous Learning Systems is the result of over a decade of focused research and studies in this emerging area which spans a number of well-known and well-established disciplines that include machine learning, system identification, data mining, fuzzy logic, neural networks, neuro-fuzzy systems, control theory and pattern recognition. The evolution of these systems has been both industry-driven with an increasing demand from sectors such as defence and security, aerospace and advanced process industries, bio-medicine and intelligent transportation, as well as research-driven – there is a strong trend of innovation of all of the above well-established research disciplines that is linked to their on-line and real-time application; their adaptability and flexibility. Providing an introduction to the key technologies, detailed technical explanations of the methodology, and an illustration of the practical relevance of the approach with a wide range of applications, this book addresses the challenges of autonomous learning systems with a systematic approach that lays the foundations for a fast growing area of research that will underpin a range of technological applications vital to both industry and society. Key features: Presents the subject systematically from explaining the fundamentals to illustrating the proposed approach with numerous applications. Covers a wide range of applications in fields including unmanned vehicles/robotics, oil refineries, chemical industry, evolving user behaviour and activity recognition. Reviews traditional fields including clustering, classification, control, fault detection and anomaly detection, filtering and estimation through the prism of evolving and autonomously learning mechanisms. Accompanied by a website hosting additional material, including the software toolbox and lecture notes. Autonomous Learning Systems provides a ‘one-stop shop’ on the subject for academics, students, researchers and practicing engineers. It is also a valuable reference for Government agencies and software developers.

《建構主義指導下的自主學習理論與實踐》彙集了建構主義理論的中心觀點，探討了如何在建構主義理論指導下進行自主學習的問題；分析了自主學習的歷史根源及發展過程，闡述了自主學習的獨有特徵，介紹了麥考姆斯、賓特裡奇等大師設計的自主學習模型；重點論述了自主學習的教學模式及其在課堂中的實際應用，並以此為契機，展示了自主學習中心建立的必要性以及構成與發展自主學習中心的基本要素。

This book looks beyond the classroom, and focuses on out-of-class autonomous use of technology for language learning, discussing the theoretical frameworks, key findings and critical issues. The proliferation of digital language learning resources and tools is forcing language education into an era of unprecedented change. The book will stimulate discussions on how to support language learners to construct quality autonomous technology-mediated out-of-class learning experience outside the classroom and raise greater awareness of and research interest in this field. Out-of-class learning constitutes an important context for human development, and active engagement in out-of-class activities is associated with successful language development. With convenient access to expanded resources, venues and learning spaces, today's learners are not as dependent on in-class learning as they used to be. Thus, a deeper understanding of the terrain of out-of-class learning is of increasing significance in the current educational era. Technology is part and parcel of out-of-class language learning, and has been a primary source that learners actively use to construct language learning experience beyond the classroom. Language learners of all ages around the world have been found to actively utilize technological resources to support their language learning beyond formal language learning contexts. Insights into learners' out-of-class autonomous use of technology for language learning are essential to our understanding of out-of-class learning and inform educators on how language learners could be better supported to maximize the educational potentials of technology to construct quality out-of-class learning experience.

Traditionally, organizations and researchers have focused on learning that occurs through formal training and development programs. However, the realities of today’s workplace suggest that it is difficult, if not impossible, for organizations to rely mainly on formal programs for developing human capital. This volume offers a broad-based treatment of autonomous learning to advance our understanding of learner-driven approaches and how organizations can support them. Contributors in industrial/organizational psychology, management, education, and entrepreneurship bring theoretical perspectives to help us understand autonomous learning and its consequences for individuals and organizations. Chapters consider informal learning, self-directed learning, learning from job challenges, mentoring, Massive Open Online Courses (MOOCs), organizational communities of practice, self-regulation, the role of feedback and errors, and how to capture value from autonomous learning. This book will appeal to scholars, researchers, and practitioners in psychology, management, training and development, and educational psychology.

Many new technologies – like RFID, GPS, and sensor networks – that dominate innovative developments in logistics are based on the idea of autonomous cooperation and control. This self-organisational concept describes „...processes of decentralized decision-making in heterarchical structures. It presumes interacting elements in non-deterministic systems, which possess the capability and possibility to render decisions. The objective of autonomous cooperation and control is the achievement of increased robustness and positive emergence of the total system due to distributed and flexible coping with dynamics and complexity“ (Hülsmann & Windt, 2007). In order to underlie these technology-driven developments with a fundamental theoretical foundation this edited volume asks for contributions and limitations of applying the principles of autonomous cooperation and control to logistics processes and systems. It intends to identify, describe, and explain – in the context of production and distribution logistics – the effects on performance and robustness, the enablers and impediments for the feasibility, the essential cause-effect-relations, etc. of concepts, methods, technologies, and routines of autonomous cooperation and control in logistics. Therefore, the analyses collected in this edited volume aim to develop a framework for finding the optimal degree as well as the upper and lower boundaries of autonomous cooperation and control of logistics processes from the different perspectives of production technology, electronics and communication engineering, informatics and mathematics, as well as management sciences and economics.