Month: September 2022

New projects funded by Connectivity Fund

Also for this call, Connectivity Fund received many applications. We are glad to announce the funded projects for this session: For having a look to the other projects granted by Connectivity Fund, check this webpage: https://tailor-network.eu/connectivity-fund/funded-projects/ The next call for Connectivity Fund will be in 4 months. The next deadline is in 15th of March …

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A Modular Framework for Hybrid Participatory Systems

Enrico Liscio – TU Delft PhD student Participatory systems aim to elicit citizens’ stances on societal discussions to inform policy making. In particular, human values are a crucial component of citizens’ stances, since they are the drivers of our opinions and behaviors. AI can enable mass participation and process large quantity of citizens’ input. However, …

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Trustworthy AI for human behavior prediction by autonomous

Julian F. Schumann – TU Delft PhD student For humans to trust autonomous vehicles, they need to have confidence in the vehicles’ ability to reliably resolve space-sharing conflicts with other traffic participants in a safe manner – such as in the case of crossing or merging paths. Planning safe and efficient interactions for autonomous vehicles …

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Graph Gaussian Processes for Interactive Robot Task Learning

Giovanni Franzese – TU Delft PhD candidate The adaptability of robot manipulators to many different tasks is currently constrained by systematic hard coding of each specific task. Recent machine learning methods like Learning from Demonstrations (LfD) and Reinforcement Learning (RL) have shown promising results in having fast reprogramming of the task using human demonstrations or …

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Multi-Objective Statistically Robust Algorithm Ranking

Jeroen G. Rook – University of Twente PhD candidate Comparing algorithms is a non-trivial task. Often, a set of representative problem instances are used to compare algorithms. However, these problem instances introduce biases in the comparison outcomes, which is often not taken into account. The confidence of the comparison can be strengthened by using statistical …

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TAILOR Handbook of Trustworthy AI

The TAILOR Handbook of Trustworthy AI is an encyclopedia of the major scientific and technical terms related to Trustworthy Artificial Intelligence. The main goal of the Handbook of Trustworthy AI is to provide non experts, especially researchers and students, an overview of the problem related to the development of ethical and trustworthy AI systems. The …

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The TAILOR roadmap shows the path towards Trustworthy AI

The TAILOR project is focussed on Trustworthy Artificial Intelligence through Learning, Optimization and Reasoning, and address topics that are currently very actively investigated. Therefore, defining a roadmap was an ambitious endeavour. The editorial team led by Marc Schoenauer, INRIA, France and Michela Milano, Bologna University have assembled voices from the TAILOR network and beyond to …

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Leslie Pack Kaelbling keynote speak at the 2nd TAILOR conference: “Doing for our robots what nature did for us”

Leslie Pack Kaelbling, Panasonic Professor of Computer Science and Engineering at the Department of Electrical Engineering and Computer Science of Massachusetts Institute of Technology, will give a keynote speak at the upcoming TAILOR conference in Prague, on Semptember 13th 2022, 14-15 (CET). Abstract We, as robot engineers, have to think hard about our role in the design …

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