Distributed Control Multi-Agent Systems
178 papers on this topic
Differentially-private Distributed Algorithms for Aggregative Games with Guaranteed Convergence
The distributed computation of a Nash equilibrium in aggregative games is gaining increased traction in recent years. Of particular interest is the mediator-free scenario where individual players...
Decentralized Nonconvex Optimization with Guaranteed Privacy and Accuracy
Privacy protection and nonconvexity are two challenging problems in decentralized optimization and learning involving sensitive data. Despite some recent advances addressing each of the two...
The effect of network topologies on fully decentralized learning: a preliminary investigation
In a decentralized machine learning system, data is typically partitioned among multiple devices or nodes, each of which trains a local model using its own data. These local models are then shared...
Decentralized Multi-Agent Active Search and Tracking when Targets Outnumber Agents
Multi-agent multi-target tracking has a wide range of applications, including wildlife patrolling, security surveillance or environment monitoring. Such algorithms often make restrictive...
Distributed Average Consensus via Noisy and Non-Coherent Over-the-Air Aggregation
Over-the-air aggregation has attracted widespread attention for its potential advantages in task-oriented applications, such as distributed sensing, learning, and consensus. In this paper, we...
CoNi-MPC: Cooperative Non-inertial Frame Based Model Predictive Control
This paper presents a novel solution for UAV control in cooperative multi-robot systems, which can be used in various scenarios such as leader-following, landing on a moving base, or specific...
Robust MADER: Decentralized Multiagent Trajectory Planner Robust to Communication Delay in Dynamic Environments
Communication delays can be catastrophic for multiagent systems. However, most existing state-of-the-art multiagent trajectory planners assume perfect communication and therefore lack a strategy...
LDSA: Learning Dynamic Subtask Assignment in Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) has made prominent progress in recent years. For training efficiency and scalability, most of the MARL algorithms make all agents share the...
Can A Single Human Supervise A Swarm of 100 Heterogeneous Robots?
An open research question has been whether a single human can supervise a true heterogeneous swarm of robots completing tasks in real world environments. A general concern is whether or not the...
Robust MADER: Decentralized and Asynchronous Multiagent Trajectory Planner Robust to Communication Delay
Although communication delays can disrupt multiagent systems, most of the existing multiagent trajectory planners lack a strategy to address this issue. State-of-the-art approaches typically...
From Explicit Communication to Tacit Cooperation:A Novel Paradigm for Cooperative MARL
Centralized training with decentralized execution (CTDE) is a widely-used learning paradigm that has achieved significant success in complex tasks. However, partial observability issues and the...
Online Parallel Multi-Task Relationship Learning via Alternating Direction Method of Multipliers
Online multi-task learning (OMTL) enhances streaming data processing by leveraging the inherent relations among multiple tasks. It can be described as an optimization problem in which a single...
Task load dependent decision referrals for joint binary classification in human-automation teams
We consider the problem of optimal decision referrals in human-automation teams performing binary classification tasks. The automation, which includes a pre-trained classifier, observes data for a...
CurvaDion: Curvature-Adaptive Distributed Orthonormalization
As language models scale to trillions of parameters, distributed training across many GPUs becomes essential, yet gradient synchronization over high-bandwidth, low-latency networks remains a...
Convergence, Consensus and Dissensus in the Weighted-Median Opinion Dynamics
Mechanistic and tractable mathematical models play a key role in understanding how social influence shapes public opinions. Recently, a weighted-median mechanism has been proposed as a new...
The Age of Gossip in Networks
A source node updates its status as a point process and also forwards its updates to a network of observer nodes. Within the network of observers, these updates are forwarded as point processes...
Composite federated learning with heterogeneous data
We propose a novel algorithm for solving the composite Federated Learning (FL) problem. This algorithm manages non-smooth regularization by strategically decoupling the proximal operator and...
Diffusion Stochastic Optimization for Min-Max Problems
The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need for a large batch...