Publications related to Autonomous virtual agents learning a cognitive model and evolving

Related publications (34)

Towards Generalizable Trajectory Prediction using Dual-Level Representation Learning and Adaptive Prompting

Alexandre Massoud Alahi, Kaouther Messaoud Ben Amor

Existing vehicle trajectory prediction models struggle with generalizability, prediction uncertainties, and handling complex interactions. It is often due to limitations like complex architectures customized for a specific dataset and inefficient multimoda ...

Institute of Electrical Engineering2025

Enhancing Critical Thinking in Education by Means of a Socratic Chatbot

Tanja Christina Käser Jacober

While large language models (LLMs) are increasingly playing a pivotal role in education by providing instantaneous, adaptive responses, their potential to promote critical thinking remains understudied. In this paper, we fill such a gap and present an inno ...

Springer Science and Business Media Deutschland GmbH2025

Accelerating Transfer Learning with Near-Data Computation on Cloud Object Stores

Rachid Guerraoui, Arsany Hany Abdelmessih Guirguis, Diana Andreea Petrescu

Storage disaggregation underlies today's cloud and is naturally complemented by pushing down some computation to storage, thus mitigating the potential network bottleneck between the storage and compute tiers. We show how ML training benefits from storage ...

Association for Computing Machinery, Inc2024

In case of doubt, one follows one's self: the implicit guidance of the embodied self-avatar

Ronan Boulic, Bruno Herbelin, Loën Boban

The sense of embodiment in virtual reality (VR) is commonly understood as the subjective experience that one's physical body is substituted by a virtual counterpart, and is typically achieved when the avatar's body, seen from a first-person view, moves lik ...

2024

Causal Influence in Federated Edge Inference

Ali H. Sayed, Mert Kayaalp, Yunus Inan

In this paper, we consider a setting where heterogeneous agents with connectivity are performing inference using unlabeled streaming data. Observed data are only partially informative about the target variable of interest. In order to overcome the uncertai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Ethological computational psychiatry: Challenges and opportunities

Mackenzie Mathis

Studying the intricacies of individual subjects' moods and cognitive processing over extended periods of time presents a formidable challenge in medicine. While much of systems neuroscience appropriately focuses on the link between neural circuit functions ...

Current Biology Ltd2024

Customizing the human-avatar mapping based on EEG error related potentials during avatar-based interaction

Olaf Blanke, José del Rocio Millán Ruiz, Ronan Boulic, Ricardo Andres Chavarriaga Lozano, Bruno Herbelin, Fumiaki Iwane, Thibault Serge Mario Porssut

Objective. A key challenge of virtual reality (VR) applications is to maintain a reliable human-avatar mapping. Users may lose the sense of controlling (sense of agency), owning (sense of body ownership), or being located (sense of self-location) inside th ...

2024

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Anastasiia Koloskova

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

EPFL2024

SIMBa: System Identification Methods Leveraging Backpropagation

Colin Neil Jones, Giancarlo Ferrari Trecate, Muhammad Zakwan, Loris Di Natale

This manuscript details and extends the system identification methods leveraging the backpropagation (SIMBa) toolbox presented in previous work, which uses well-established machine learning tools for discrete-time linear multistep-ahead state-space system ...

2024

Social Opinion Formation and Decision Making Under Communication Trends

Ali H. Sayed, Virginia Bordignon, Mert Kayaalp

This work studies the learning process over social networks under partial and random information sharing. In traditional social learning models, agents exchange full belief information with each other while trying to infer the true state of nature. We stud ...

Ieee-Inst Electrical Electronics Engineers Inc2024

An immersive virtual reality tool for assessing left and right unilateral spatial neglect

Olaf Blanke, Andrea Serino, Roberta Ronchi

The reported rate of the occurrence of unilateral spatial neglect (USN) is highly variable likely due to the lack of validity and low sensitivity of classical tools used to assess it. Virtual reality (VR) assessments try to overcome these limitations by pr ...

Wiley2024

Neurobiological and metabolic basis of motivation and effort-based decision-making - A human 1H-MRS, fMRI and machine learning study

Arthur Barakat

Motivation is a multifaceted phenomenon that we explore within the framework of decision-making. Through this cognitive process, actions are directed towards specific goals by performing a trade-off between the cost and benefit of an action. The dorsomedia ...

EPFL2024

Stochastic pairwise preference convergence in Bayesian agents

Max-Olivier Hongler

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 ...

2024

InNeRF360: Text-Guided 3D-Consistent Object Inpainting on 360° Neural Radiance Fields

Sabine Süsstrunk, Tong Zhang, Dongqing Wang

We propose InNeRF360, an automatic system that accurately removes text-specified objects from 360 • Neural Radiance Fields (NeRF). The challenge is to effectively remove objects while inpainting perceptually consistent content for the missing regions, whic ...

IEEE2024

Organ Neuroprosthetics: Connecting Transplanted and Artificial Organs with the Nervous System

Silvestro Micera

Implantable neural interfaces with the central and peripheral nervous systems are currently used to restore sensory, motor, and cognitive functions in disabled people with very promising results. They have also been used to modulate autonomic activities to ...

Wiley2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Mattia Atzeni

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

EPFL2024

From finger animation to full-body embodiment of avatars with different morphologies and proportions

Mathias Guy Delahaye

VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world. This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR. At the advent of ...

EPFL2023

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

Hala Khodr

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 ...

EPFL2023

Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations

Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Kynthia Chamilothori, Seungryong Kim, Bahar Aydemir

Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...

2023