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 …
Trustworthy AI for human behavior prediction by autonomous vehicles Read More »
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 …
Graph Gaussian Processes for Interactive Robot Task Learning Read More »
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 …
Multi-Objective Statistically Robust Algorithm Ranking Read More »
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 …
On 13th and 14th of September, TAILOR had its second annual conference. This time the conference was hosted in Prague, at the beautiful location of Charles University. The major objectives of the conference was to discuss about what TAILOR did so far, to make a plan for the next year, and finally to meet in …
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 …
During the week from 13th to 17th of June, the 19th EurAI Advanced Course on AI (ACAI) and 2nd TAILOR summer school was organised in Barcelona. This joint initiative was devoted to the themes of explainable and trustworthy AI and organized by Carles Sierra and Karina Gibert from the Intelligent Data Science and Artificial Intelligence Research Center at Universitat …
Impressions from The Joint TAILOR-EurAI Summer school in Barcelona Read More »
Guest Editors Roberta Calegari, Alma Mater Studiorum-Università di Bologna, Italy – roberta.calegari@unibo.it Fosca Giannotti, Scuola Normale Superiore, Italy – fosca.giannotti@isti.cnr.it Michela Milano, Alma Mater Studiorum-Università di Bologna, Italy – michela.milano@unibo.it Francesca Pratesi, National Research Council, Italy – francesca.pratesi@isti.cnr.it This special issue calls for surveys that address at least one dimension of Trustworthy Artificial Intelligence (TAI) and provide a broad and …
Call for Papers: ACM Computing Surveys – Special Issue on Trustworthy AI Read More »
On the 10th of May 2022, the fourth joint “Theme Development Workshop” (TDW) focused on the latest trends and challenges of “AI for Future Manufacturing”. The discussion hosted close to 80 key experts from 20 European countries, from both academia and the manufacturing sector, as well as other relevant stakeholders. The participants had one primary, but still very challenging …
Report from Theme Development Workshop “AI for Future Manufacturing” Read More »
Meta-learning aims to leverage the experience from previous tasks to solve new tasks using only little training data, train faster and/or get better performance. The proposed challenge focuses on “cross-domain meta-learning” for few-shot image classification using a novel “any-way” and “any-shot” setting. This challenge is part of TAILOR WP2 (see more information here). Goal The …
