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Related publications (30)

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Exploiting environmental signals to enable policy correlation in large-scale decentralized systems

Boi Faltings, Panayiotis Danassis, Zeki Doruk Erden

Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite of the bleak prediction of non-cooperative game theory. On top of that, rea ...

SPRINGER2022

Improved Cooperation by Exploiting a Common Signal

Boi Faltings, Panayiotis Danassis, Zeki Doruk Erden

International Foundation for Autonomous Agents and Multiagent Systems2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Bio-inspired Reflex System for Learning Visual Information for Resilient Robotic Manipulation

Josephine Anna Eleanor Hughes, Kai Christian Junge

Humans have an incredible sense of self-preservation that is both instilled, and also learned through experience. One system which contributes to this is the pain and reflex system which both minimizes damage through involuntary reflex ac- tions and also s ...

2022

Mapping forest in the Swiss Alps treeline ecotone with explainable deep learning

Devis Tuia, Benjamin Alexander Kellenberger, Thiên-Anh Claris Nguyen

Forest maps are essential to understand forest dynamics. Due to the increasing availability of remote sensing data and machine learning models like convolutional neural networks, forest maps can these days be created on large scales with high accuracy. Com ...

Elsevier2022

The role of feedback and guidance as intervention methods to foster computational thinking in educational robotics learning activities for primary school

Francesco Mondada, Laila Abdelsalam El-Hamamsy, Christian Giang, Morgane Solène Denise Chevalier, Vaios Papaspyros, Jean-Philippe Pellet, Evgeniia Bonnet

Computational thinking (CT) is considered an emerging competence domain linked to 21st-century competences, and educational robotics (ER) is increasingly recognised as a tool to develop CT competences. This is why researchers recommend developing intervent ...

2022

Social Learning with Disparate Hypotheses

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents. In this setup, each agent receives data that might be generated from a different hypothesis (or state) than the data other agents receive. In c ...

IEEE2022

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Pierre Dillenbourg, Jauwairia Nasir, Aditi Kothiyal, Mortadha Abderrahim

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

2022

Improving filling level classification with adversarial training

Pascal Frossard, Apostolos Modas, Andrea Cavallaro

We investigate the problem of classifying - from a single image the level of content in a cup or a drinking glass. This problem is made challenging by several ambiguities caused by transparencies, shape variations and partial occlusions, and by the availab ...

IEEE2021

Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-specific Scaling

Paolo Prandoni

In communication systems, it is crucial to estimate the perceived quality of audio and speech. The industrial standards for many years have been PESQ, 3QUEST, and POLQA, which are intrusive methods. This restricts the possibilities of using these metrics i ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021