Publications related to A Hamilton-Jacobi Formulation for Cooperative Control of Multi-Agent Systems

Related publications (27)

Stochastic pairwise preference convergence in Bayesian agents

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

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

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

Networked Signal and Information Processing: Learning by multiagent systems

Ali H. Sayed, Stefan Vlaski

This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Melanie Nicole Zeilinger, Danilo Saccani

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

IEEE2023

Challenges and approaches in bridging the biomimicry gap in biohybrid systems of fish and robots

Vaios Papaspyros

As the field of ethology advances, especially over the past two decades, the role of animal-robot interaction tools has increasingly become essential. This importance arises from the need for controlled, repetitive, repeatable, and long-duration experiment ...

EPFL2023

A subcellular biochemical model for T6SS dynamics reveals winning competitive strategies

Yuexia Luna Lin

The type VI secretion system (T6SS) is a broadly distributed interbacterial weapon that can be used to eliminate competing bacterial populations. Although unarmed target populations are typically used to study T6SS function in vitro, bacteria most likely e ...

OXFORD UNIV PRESS2023

Impact of Redundancy on Resilience in Distributed Optimization and Learning

Nirupam Gupta, Shuo Liu

This paper considers the problem of resilient distributed optimization and stochastic learning in a server-based architecture. The system comprises a server and multiple agents, where each agent has its own local cost function. The agents collaborate with ...

Assoc Computing Machinery2023

Partial Information Sharing Over Social Learning Networks

Ali H. Sayed, Virginia Bordignon

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

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

Discovering Influencers in Opinion Formation Over Social Graphs

Ali H. Sayed, Mert Kayaalp, Valentina Shumovskaia

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 ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

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

Auke Ijspeert, Pavan P Ramdya

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 ...

AMER ASSOC ADVANCEMENT SCIENCE2023

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

Christoph Koch, Zilu Tian, Peter Lindner

We generalize the bulk-synchronous parallel (BSP) processing model to make it better support agent-based simulations. Such simulations frequently exhibit hierarchical structure in their communication patterns which can be exploited to improve performance. ...

2023

Equilibria in Network Constrained Energy Markets

Leonardo Massai

We study an energy market composed of producers who compete to supply energy to different markets and want to maximize their profits. The energy market is modeled by a graph representing a constrained power network where nodes represent the markets and lin ...

Elsevier2023

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

Zilu Tian

Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...

EPFL2023

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Yuejiang Liu

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 ...

EPFL2023

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

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 ...

International Foundation for Autonomous Agents and Multiagent Systems2022

Meta Navigation Functions: Adaptive Associations for Coordination of Multi-Agent Systems

Matin Macktoobian

In this paper, we introduce a new class of potential fields, i.e., meta navigation functions (MNFs) to coordinate multi-agent systems. Thanks to the MNF formulation, agents can contribute to each other's coordination via partial and/or total associations, ...

IEEE2022

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