133,384 research outputs found
Symbol Emergence in Robotics: A Survey
Humans can learn the use of language through physical interaction with their
environment and semiotic communication with other people. It is very important
to obtain a computational understanding of how humans can form a symbol system
and obtain semiotic skills through their autonomous mental development.
Recently, many studies have been conducted on the construction of robotic
systems and machine-learning methods that can learn the use of language through
embodied multimodal interaction with their environment and other systems.
Understanding human social interactions and developing a robot that can
smoothly communicate with human users in the long term, requires an
understanding of the dynamics of symbol systems and is crucially important. The
embodied cognition and social interaction of participants gradually change a
symbol system in a constructive manner. In this paper, we introduce a field of
research called symbol emergence in robotics (SER). SER is a constructive
approach towards an emergent symbol system. The emergent symbol system is
socially self-organized through both semiotic communications and physical
interactions with autonomous cognitive developmental agents, i.e., humans and
developmental robots. Specifically, we describe some state-of-art research
topics concerning SER, e.g., multimodal categorization, word discovery, and a
double articulation analysis, that enable a robot to obtain words and their
embodied meanings from raw sensory--motor information, including visual
information, haptic information, auditory information, and acoustic speech
signals, in a totally unsupervised manner. Finally, we suggest future
directions of research in SER.Comment: submitted to Advanced Robotic
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent âdevicesâ, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew âcognitive devicesâ are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
The Art of Knowledge Exchange: A Results-Focused Planning Guide for Development Practitioners
Designing and implementing knowledge exchange initiatives can be a big undertaking. This guide takes the guesswork out of the process by breaking it down into simple steps and providing tools to help you play a more effective role as knowledge connector and learning facilitator
The Internet-of-Things Meets Business Process Management: Mutual Benefits and Challenges
The Internet of Things (IoT) refers to a network of connected devices
collecting and exchanging data over the Internet. These things can be
artificial or natural, and interact as autonomous agents forming a complex
system. In turn, Business Process Management (BPM) was established to analyze,
discover, design, implement, execute, monitor and evolve collaborative business
processes within and across organizations. While the IoT and BPM have been
regarded as separate topics in research and practice, we strongly believe that
the management of IoT applications will strongly benefit from BPM concepts,
methods and technologies on the one hand; on the other one, the IoT poses
challenges that will require enhancements and extensions of the current
state-of-the-art in the BPM field. In this paper, we question to what extent
these two paradigms can be combined and we discuss the emerging challenges
The emergence of information systems: a communication-based theory
An information system is more than just the information technology; it is the system that emerges from the complex interactions and relationships between the information technology and the organization. However, what impact information technology has on an organization and how organizational structures and organizational change influence information technology remains an open question. We propose a theory to explain how communication structures emerge and adapt to environmental changes. We operationalize the interplay of information technology and organization as language communities whose members use and develop domain-specific languages for communication. Our theory is anchored in the philosophy of language. In developing it as an emergent perspective, we argue that information systems are self-organizing and that control of this ability is disseminated throughout the system itself, to the members of the language community. Information technology influences the dynamics of this adaptation process as a fundamental constraint leading to perturbations for the information system. We demonstrate how this view is separated from the entanglement in practice perspective and show that this understanding has far-reaching consequences for developing, managing, and examining information systems
Living labs as a driver for change in regional television
Traditional television production and distribution organizations are increasingly being challenged by a rapidly changing technological environment. These evolutions force the television industry to leave their comfort zone. This context in mind, regional television broadcasters often lack the resources, knowledge and organizational flexibility to cope with this external pressure. In this paper, we discuss the use of Living Labs as âinnovation intermediariesâ and âchange facilitatorsâ that foster and enable user-centric innovation development processes, both inside and outside the organization. This phenomenon is approached from both an open innovation and a user innovation point of view. This paper considers Living Labs as open innovation ecosystems, enabling organizations to reach out and collaborate with their (potential) audience and other external actors, but also as an open âbattle arenaâ for the organization itself. The Living Lab process governs different expectations and enables conflicting opinions to come together and to steadily grow towards a mutual solution. Moreover, the innovation development process in the Living Lab seems to have innovation spill-over effects on the organizational level, catalyzing a broader organizational change
How Resilient Are Our Societies? Analyses, Models, and Preliminary Results
Traditional social organizations such as those for the management of
healthcare and civil defence are the result of designs and realizations that
matched well with an operational context considerably different from the one we
are experiencing today: A simpler world, characterized by a greater amount of
resources to match less users producing lower peaks of requests. The new
context reveals all the fragility of our societies: unmanageability is just
around the corner unless we do not complement the "old recipes" with smarter
forms of social organization. Here we analyze this problem and propose a
refinement to our fractal social organizations as a model for resilient
cyber-physical societies. Evidence to our claims is provided by simulating our
model in terms of multi-agent systems.Comment: Paper submitted for publication in the Proc. of SERENE 2015
(http://serene.disim.univaq.it/2015/
Computational and Robotic Models of Early Language Development: A Review
We review computational and robotics models of early language learning and
development. We first explain why and how these models are used to understand
better how children learn language. We argue that they provide concrete
theories of language learning as a complex dynamic system, complementing
traditional methods in psychology and linguistics. We review different modeling
formalisms, grounded in techniques from machine learning and artificial
intelligence such as Bayesian and neural network approaches. We then discuss
their role in understanding several key mechanisms of language development:
cross-situational statistical learning, embodiment, situated social
interaction, intrinsically motivated learning, and cultural evolution. We
conclude by discussing future challenges for research, including modeling of
large-scale empirical data about language acquisition in real-world
environments.
Keywords: Early language learning, Computational and robotic models, machine
learning, development, embodiment, social interaction, intrinsic motivation,
self-organization, dynamical systems, complexity.Comment: to appear in International Handbook on Language Development, ed. J.
Horst and J. von Koss Torkildsen, Routledg
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