Publications related to Stochastic pairwise preference convergence in Bayesian agents

Augmenting large language models with chemistry tools

Philippe Schwaller, Oliver Tobias Schilter, Andres Camilo Marulanda Bran, Carlo Baldassari

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

Nature Portfolio2024

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

Multi-agent actor-critic with time dynamical opponent model

Olga Fink, Qin Wang

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 ...

ELSEVIER2023

Multi-agent Learning with Privacy Guarantees

Elsa Rizk

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 ...

EPFL2023

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

Nirupam Gupta

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

f

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

Piscataway2023

Scalable Multi-agent Coordination and Resource Sharing

Panayiotis Danassis

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 ...

EPFL2022

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

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Volkan Cevher, Kimon Antonakopoulos, Ya-Ping Hsieh

We examine the problem of regret minimization when the learner is involved in a continuous game with other optimizing agents: in this case, if all players follow a no-regret algorithm, it is possible to achieve significantly lower regret relative to fully ...

2022

Competing Adaptive Networks

Ali H. Sayed, Stefan Vlaski

Adaptive networks have the capability to pursue solutions of global stochastic optimization problems by relying only local interactions within neighborhoods. The diffusion of information through repeated interactions allows for globally optimal behavior, w ...

IEEE2021

ReMoTe-S. Residential Mobility of Tenants in Switzerland: an agent-based model

Claudia Rebeca Binder Signer, Anna Pagani, Emanuele Massaro, Francesco Ballestrazzi

Accounting for a fourth of the CO2 emissions and total energy consumption in Switzerland (IEA, 2018), housing plays a crucial role in the transition towards the sustainability of urban systems. Although new technologies have been developed to tackle the en ...

2021

Stochastic pairwise preference convergence in Bayesian agents

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Augmenting large language models with chemistry tools

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

Multi-agent actor-critic with time dynamical opponent model

Multi-agent Learning with Privacy Guarantees

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

Scalable Multi-agent Coordination and Resource Sharing

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

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Competing Adaptive Networks

ReMoTe-S. Residential Mobility of Tenants in Switzerland: an agent-based model

Augmenting large language models with chemistry tools

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

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

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Multi-agent Learning with Privacy Guarantees

Scalable Multi-agent Coordination and Resource Sharing

Multi-agent actor-critic with time dynamical opponent model

Competing Adaptive Networks

ReMoTe-S. Residential Mobility of Tenants in Switzerland: an agent-based model

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