Sökning: "distributed artificial intelligence"

Visar resultat 1 - 5 av 27 avhandlingar innehållade orden distributed artificial intelligence.

  1. 1. På AI-teknikens axlar : om kunskapssociologin och stark artificiell intelligens

    Författare :Peter Kåhre; Gunnar Andersson; Tom Ziemke; Lunds universitet; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Gregory Bateson; James Wertsch.; Yrjö Engeström; Katherine N. Hayles; Lucy Suchman; Hubert Dreyfus; John Searle; David Bloor; Lev Vygotsky; Niklas Luhmann; Chinese room; Turing test; socionics; darwinism; emergence; relativism; posthumanism; environmentalism; situationism; social communication; second order cybernetics; systems theory; sociology of knowledge; connectionism; Strong artificial intelligence; distributed artificial intelligence; Sociology; Sociologi; Library and Information Science; Biblioteks- och informationsvetenskap; Filosofi; Practical Philosophy;

    Sammanfattning : This dissertation is concerned with Sociology’s stance in the debate on Strong Artificial Intelligence, i.e. such AI that is able to shape new knowledge without human interference. There is a need for sociologists to realize the difference between two approaches to constructing AI systems: Symbolic AI (or Classic AI) and Distributed AI – DAI. LÄS MER

  3. 2. Distributed Intelligence-Assisted Autonomic Context-Information Management : A context-based approach to handling vast amounts of heterogeneous IoT data

    Författare :Hasibur Rahman; Rahim Rahmani; Theo Kanter; Elhadi Shakshuki; Stockholms universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Internet of Things; Context information; Intelligence; Edge computing; Distributed computing; Computer and Systems Sciences; data- och systemvetenskap;

    Sammanfattning : As an implication of rapid growth in Internet-of-Things (IoT) data, current focus has shifted towards utilizing and analysing the data in order to make sense of the data. The aim of which is to make instantaneous, automated, and informed decisions that will drive the future IoT. LÄS MER

  4. 3. På AI-teknikens axlar : Om kunskapssociologin och stark artificiell intelligens

    Författare :Peter Kåhre; Sociologi; []
    Nyckelord :SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; James Wertsch; Gregory Bateson; Yrjö Engeström; Katherine N. Hayles; Lucy Suchman; Hubert Dreyfus; John Searle; David Bloor; Lev Vygotsky; Niklas Luhmann; Chinese room; Turing test; socionics; darwinism; emergence; relativism; posthumanism; environmentalism; situationism; social communication; second order cybernetics; systems theory; sociology of knowledge; connectionism; Strong artificial intelligence; distributed artificial intelligence;

    Sammanfattning : This dissertation is concerned with Sociology’s stance in the debate on Strong Artificial Intelligence, i.e. such AI that is able to shape new knowledge without human interference. There is a need for sociologists to realize the difference between two approaches to constructing AI systems: Symbolic AI (or Classic AI) and Distributed AI – DAI. LÄS MER

  5. 4. Data-Centric Network of Things : A Method for Exploiting the Massive Amount of Heterogeneous Data of Internet of Things in Support of Services

    Författare :Bin Xiao; Rahim Rahmani; Theo Kanter; Mika Ylianttila; Stockholms universitet; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Internet of Things; Big Data; Artificial Intelligence; Data Supply; Distributed System; Computer and Systems Sciences; data- och systemvetenskap;

    Sammanfattning : Internet of things (IoT) generates massive amount of heterogeneous data, which should be efficiently utilized to support services in different domains. Specifically, data need to be supplied to services by understanding the needs of services and by understanding the environment changes, so that necessary data can be provided efficiently but without overfeeding. LÄS MER

  7. 5. Machine learning for identification of brain activity patterns with applications in gentle touch processing

    Författare :Malin Björnsdotter Åberg; Göteborgs universitet; []
    Nyckelord :Somatosensory; Machine learning; Pattern recognition; fMRI; Support vector machines; Neuroscience; Brain; BOLD; Signal processing; Artificial intelligence; Touch; Human; Unmyelinated; Sensory; Affective;

    Sammanfattning : Since the first mention of artificial intelligence in the 1950s, the field of machine learning has provided increasingly appealing tools for recognition of otherwise unintelligible pattern representations in complex data structures. Human brain activity, acquired using functional magnetic resonance imaging (fMRI), is a prime example of such complex data where the utility of pattern recognition has been demonstrated in a wide range of studies recently (Haynes et al. LÄS MER