Orthos: A Trustworthy AI Framework for Data Acquisition

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Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

With the prevalence of smartphones, watches, and Internet of Things (IoT) devices, the ability to track their positions is becoming increasingly important. For many indoor positioning systems (IPSs), providing an uninterrupted flow of information in real-t ...

Robotics and neuroscience are sister disciplines that both aim to understand how agile, efficient, and robust locomotion can be achieved in autonomous agents. Robotics has already benefitted from neuromechanical principles discovered by investigating anima ...

In multi-agent reinforcement learning, multiple agents learn simultaneously while interacting with a common environment and each other. Since the agents adapt their policies during learning, not only the behavior of a single agent becomes non-stationary, b ...

In this chapter, we present a review of recent progress in the modeling of lightning strikes to tall structures. Since some tall structures are struck by lightning several tens of times per year, they can be used as ground-truth to measure and calibrate th ...

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

This is the experimental data used in manuscript: "Rock anisotropy promotes hydraulic fracture containment at depth". This data set has 5 folders: K1, T2, M3 and M4 contain the raw data collected by active acoustic monitoring system and various pumps and t ...

The adaptive social learning paradigm helps model how networked agents are able to form opinions on a state of nature and track its drifts in a changing environment. In this framework, the agents repeatedly update their beliefs based on private observation ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

In this article, we study the problem of Byzantine fault-tolerance in a federated optimization setting, where there is a group of agents communicating with a centralized coordinator. We allow up to

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Byzantine-faulty agents, which may not follow a prescr ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsup ...

Nowadays, usage-based acquisition models for e-books, as PDA and EBA, are quite spread and allow libraries to offer wider collections, without acquiring them. A PDA with Ebook Central was implemented in 2019 and a first EBA with Wiley in 2021. The EPFL Lib ...

A plethora of real world problems consist of a number of agents that interact, learn, cooperate, coordinate, and compete with others in ever more complex environments. Examples include autonomous vehicles, robotic agents, intelligent infrastructure, IoT de ...

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 ...

Nowadays, transmission system operators require higher degree of observability in real-time to gain situational awareness and improve the decision-making process to guarantee a safe and reliable operation. Digitalization of energy systems allows utilities ...

Research problem: Housing is responsible for a considerable part of global resource consumption. In Switzerland, it accounts for almost one third of the country's CO2 emissions and half of the total energy demand. Thus, housing plays an important role in t ...

In this article, we propose a novel approach for the localization of electromagnetic interference (EMI) sources based on the concept of compressive sensing and metalenses. We show that using the spatial and frequency dispersion offered by the metalens, we ...

The classical electromagnetic time reversal (EMTR) fault location method in power systems can be time consuming, especially when a high location accuracy is desired. To cope with this issue, the concept of EMTR in mismatched media has recently been introdu ...

Orthos: A Trustworthy AI Framework for Data Acquisition

Chat with Graph Search

Stochastic pairwise preference convergence in Bayesian agents

Indoor Real-time localization system design for Internet of Things applications

The neuromechanics of animal locomotion: From biology to robotics and back

Multi-agent actor-critic with time dynamical opponent model

Modeling lightning strikes to tall towers

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Dataset for manuscript: Rock anisotropy promotes hydraulic fracture containment at depth

Discovering Influencers in Opinion Formation Over Social Graphs

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy

Multi-agent Learning with Privacy Guarantees

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Mechanical intelligence for learning embodied sensor-object relationships

Patron-Driven Acquisition et Evidence-Based Acquisition: Comment implémenter ces modèles afin d’étendre l’offre documentaire dans une bibliothèque ?

Scalable Multi-agent Coordination and Resource Sharing

Social Learning with Disparate Hypotheses

State-of-the-art of data collection, analytics, and future needs of transmission utilities worldwide to account for the continuous growth of sensing data

Towards sufficiency in housing: Agent-based model and transition scenarios

A Compressive Sensing Framework for EMI Source Localization Using a Metalens Structure: Localization Beyond the Diffraction Limit

A Data-Driven Fault Location Algorithm Based on the Electromagnetic Time Reversal in Mismatched Media