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Concept

Intelligence distribuée

Publications associées (30)

Co-Design Optimisation of Morphing Topology and Control of Winged Drones

Dario Floreano, Valentin Wüest

The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, m ...

IEEE2024

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

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

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Silvestro Micera, Simone Romeni

Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon ...

IOP Publishing Ltd2023

Morphological flexibility in robotic systems through physical polygon meshing

Jamie Paik, Christoph Heinrich Belke, Kevin Andrew Holdcroft

Shape-changing robots adapt their own morphology to address a wider range of functions or environments than is possible with a fixed or rigid structure. Akin to biological organisms, the ability to alter shape or configuration emerges from the underlying m ...

Nature Portfolio2023

Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain

Georg Michael Joachim Starke

The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain- ...

2023

Quantization for Decentralized Learning Under Subspace Constraints

Ali H. Sayed, Stefan Vlaski, Roula Nassif

In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

C-shells: Deployable Gridshells with Curved Beams

Mark Pauly, Francis Julian Panetta, Yingying Ren, Quentin Christian Becker, Seiichi Eduardo Suzuki Erazo, Davide Pellis

We introduce a computational pipeline for simulating and designing C-shells, a new class of planar-to-spatial deployable linkage structures. A C-shell is composed of curved flexible beams connected at rotational joints that can be assembled in a stress-fre ...

Association for Computing Machinery (ACM)2023

Multi-agent actor-critic with time dynamical opponent model

Olga Fink

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 ...

2023

Cellulan World: Interactive Platform to Learn Swarm Behaviors

Pierre Dillenbourg, Barbara Bruno, Aditi Kothiyal, Hala Khodr

Swarming behaviors are ubiquitous in nature, and an important topic to teach and learn. In the learning sciences domain of complex systems understanding, studies have shown that novices tend to assume that centralized control and leadership should exist wh ...

IFAAMAS2022

On the Scalability of Vision-based Drone Swarms in the Presence of Occlusions

Dario Floreano, Fabian Maximilian Schilling, Enrica Soria

Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...

2022

A Critical Re-evaluation of Neural Methods for Entity Alignment

Robert West, Akhil Arora, Alberto Garcia Duran

Neural methods have become the de-facto choice for the vast majority of data analysis tasks, and entity alignment (EA) is no exception. Not surprisingly, more than 50 different neural EA methods have been published since 2017. However, surprisingly, an ana ...

ASSOC COMPUTING MACHINERY2022

Vision-based Flocking in Aerial Robot Swarms

Fabian Maximilian Schilling

Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...

EPFL2022

Model Predictive Control of Aerial Swarms

Enrica Soria

Aerial robot swarms can have a large socio-economic impact. They can perform time-critical missions faster than a single robot and access dangerous environments without compromising human safety. However, swarm deployment is often limited to free environme ...

EPFL2022

Swarms of flying robots in unknown environments

Enrica Soria

An optimal planning algorithm enables swarms of flying robots to explore unknown environments autonomously and safely. ...

2022

Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction

Mathieu Salzmann

We introduce the task of action-driven stochastic human motion prediction, which aims to predict multiple plausible future motions given a sequence of action labels and a short motion history. This differs from existing works, which predict motions that ei ...

IEEE COMPUTER SOC2022

Dual-function engineering to construct ultra-stable anodes for potassium-ion hybrid capacitors: N, O-doped porous carbon spheres

Kangning Zhao, Yanan Chen

Heteroatom doping engineering is deemed to be an adoptable strategy to boost the potassium (K) storage performance of carbonaceous materials. The inevitable issue for this strategy lies in the huge volume expansion originated from the large radius of K+. I ...

Elsevier2022

Tales from a Robotic World. How Intelligent Machines Will Shape Our Future

Dario Floreano, Nicola Nosengo

Stories from the future of intelligent machines—from rescue drones to robot spouses—and accounts of cutting-edge research that could make it all possible. Tech prognosticators promised us robots—autonomous humanoids that could carry out any number of tasks ...

MIT Press2022

Microscopic field theory for structure formation in systems of self-propelled particles with generic torques

Ignacio Pagonabarraga Mora, Elena Sesé Sansa

We derive a dynamical field theory for self-propelled particles subjected to generic torques and forces by explicitly coarse-graining their microscopic dynamics, described by a many-body Fokker-Planck equation. The model includes both intrinsic torques ind ...

AIP Publishing2022

Collective behavior and emerging patterns in dense dry aligning active matter

Elena Sesé Sansa

In this thesis, we study systems of active particles interacting via generic torques of different nature. We analyze the phase behavior of these systems, which results from the interplay between self-propulsion, excluded-volume and torques. We tackle the p ...

EPFL2022