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Michael Schumacher

Researcher at University of Applied Sciences Western Switzerland

Publications -  154
Citations -  3724

Michael Schumacher is an academic researcher from University of Applied Sciences Western Switzerland. The author has contributed to research in topics: Multi-agent system & Autonomous agent. The author has an hindex of 28, co-authored 154 publications receiving 3130 citations. Previous affiliations of Michael Schumacher include Lahti University of Applied Sciences & Open University.

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Journal ArticleDOI

Involvement of β-catenin and unusual behavior of CBP and p300 in glucocorticosteroid signaling in Schwann cells

TL;DR: The results suggest the formation of a GR-coactivator complex within Schwann cells, indicating that glucocorticosteroids may act by means of unusual partners in the nervous system, and a repressive effect of p300 on nuclear receptors is shown.
Book ChapterDOI

Explainable Multi-Agent Systems Through Blockchain Technology.

TL;DR: A joint approach employing both blockchain technology (BCT) and explainability in the decision-making process of MAS can be made more transparent and secure and thereby trustworthy from the human user standpoint by doing so.
Journal ArticleDOI

The open D1NAMO dataset: A multi-modal dataset for research on non-invasive type 1 diabetes management

TL;DR: This dataset, which was acquired on 20 healthy subjects and 9 patients with type-1 diabetes, consists of ECG, breathing, and accelerometer signals, as well as glucose measurements and annotated food pictures and is opened to the scientific community to allow the development and evaluation of diabetes management algorithms.
Journal ArticleDOI

Real-time multi-agent systems for telerehabilitation scenarios

TL;DR: A focus group with experts in physiotherapy and telerehabilitation is presented, debating on the requirements, current techniques and technologies developed to facilitate and enhance the effectiveness of telere rehabilitation, and the still open challenges.
Book ChapterDOI

Agent-Based Explanations in AI: Towards an Abstract Framework.

TL;DR: This paper proposes an abstract and formal framework for XAI-based MAS, reconciling notions, and results from the literature.