Decentralised system
View article: Towards ICT-Enabled Multi-agent Based Operations in Local Energy Communities: A Proof of Concept
Towards ICT-Enabled Multi-agent Based Operations in Local Energy Communities: A Proof of Concept Open
View article: EnergyFlow: Predictive trading platform for decentralized energy exchange
EnergyFlow: Predictive trading platform for decentralized energy exchange Open
View article: "Adaptive Event--Triggered Consensus Control of Heterogeneous Multi--Robot Systems Based on Deep Reinforcement Learning"
"Adaptive Event--Triggered Consensus Control of Heterogeneous Multi--Robot Systems Based on Deep Reinforcement Learning" Open
" The coordinated control of heterogeneous multi\u2011robot systems is an important research direction in the current field of intelligent systems and has broad application prospects in industrial manufacturing, disaster rescue, and int…
View article: Robust Adaptive Model Predictive Control for Tracking in Interconnected Systems via Distributed Optimization
Robust Adaptive Model Predictive Control for Tracking in Interconnected Systems via Distributed Optimization Open
This study presents a novel Distributed Robust Adaptive Model Predictive Control (DRAMPC) for tracking in multi‐agent systems. The framework is designed to work with dynamically coupled subsystems and limited communication, which is restri…
View article: Resilient Charging Infrastructure via Decentralized Coordination of Electric Vehicles at Scale
Resilient Charging Infrastructure via Decentralized Coordination of Electric Vehicles at Scale Open
The rapid adoption of electric vehicles (EVs) introduces major challenges for decentralized charging control. Existing decentralized approaches efficiently coordinate a large number of EVs to select charging stations while reducing energy …
View article: DualSynNet: A Dual-Center Collaborative Space Network with Federated Graph Reinforcement Learning for Autonomous Task Optimization
DualSynNet: A Dual-Center Collaborative Space Network with Federated Graph Reinforcement Learning for Autonomous Task Optimization Open
Recent space exploration roadmaps from China, the United States, and Russia highlight the establishment of Mars bases as a major objective. Future deep-space missions will span the inner solar system and extend beyond the asteroid belt, de…
View article: Decentralized Shepherding of Non-Cohesive Swarms Through Cluttered Environments via Deep Reinforcement Learning
Decentralized Shepherding of Non-Cohesive Swarms Through Cluttered Environments via Deep Reinforcement Learning Open
This paper investigates decentralized shepherding in cluttered environments, where a limited number of herders must guide a larger group of non-cohesive, diffusive targets toward a goal region in the presence of static obstacles. A hierarc…
View article: Deep reinforcement learning for multi-agent coordination
Deep reinforcement learning for multi-agent coordination Open
We address the challenge of coordinating multiple robots in narrow and confined environments, where congestion and interference often hinder collective task performance. Drawing inspiration from insect colonies, which achieve robust coordi…
View article: A Blockchain-Based Architecture for Energy Trading to Enhance Power Grid Stability
A Blockchain-Based Architecture for Energy Trading to Enhance Power Grid Stability Open
The integration of renewable energy sources (RES) and distributed energy resources (DER) into local energy markets is transforming modern power grids toward a decentralized architecture. To enhance the efficiency of decentralized energy tr…
View article: Toward generic control for soft robotic systems
Toward generic control for soft robotic systems Open
Soft robotics has advanced rapidly, yet its control methods remain fragmented: different morphologies and actuation schemes still require task-specific controllers, hindering theoretical integration and large-scale deployment. A generic co…
View article: Toward generic control for soft robotic systems
Toward generic control for soft robotic systems Open
Soft robotics has advanced rapidly, yet its control methods remain fragmented: different morphologies and actuation schemes still require task-specific controllers, hindering theoretical integration and large-scale deployment. A generic co…
View article: Cost-Effective automatic generation control for Renewable-dominated grids: Multi-Agent deep reinforcement learning approach
Cost-Effective automatic generation control for Renewable-dominated grids: Multi-Agent deep reinforcement learning approach Open
As power systems continue to increase in complexity, real-time frequency control has become progressively more critical for balancing power supply and demand by modulating generating unit outputs. This paper proposes a data-driven Automati…
View article: Multi-Agent Cross-Entropy Method with Monotonic Nonlinear Critic Decomposition
Multi-Agent Cross-Entropy Method with Monotonic Nonlinear Critic Decomposition Open
Cooperative multi-agent reinforcement learning (MARL) commonly adopts centralized training with decentralized execution (CTDE), where centralized critics leverage global information to guide decentralized actors. However, centralized-decen…
View article: Multi-Agent Cross-Entropy Method with Monotonic Nonlinear Critic Decomposition
Multi-Agent Cross-Entropy Method with Monotonic Nonlinear Critic Decomposition Open
Cooperative multi-agent reinforcement learning (MARL) commonly adopts centralized training with decentralized execution (CTDE), where centralized critics leverage global information to guide decentralized actors. However, centralized-decen…
View article: Mobile robot replacement in multi-robot fault-tolerant formation
Mobile robot replacement in multi-robot fault-tolerant formation Open
Formation control in multi-robot systems (MRS) is essential for collaborative transport, environmental surveillance, material handling, and distributed monitoring. A major challenge in MRS is maintaining predefined formations or cooperativ…
View article: ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning
ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning Open
This paper revisits alternating low-rank updates for federated fine-tuning and examines their behavior in decentralized federated learning (DFL). While alternating the LoRA matrices has been shown to stabilize aggregation in centralized FL…
View article: Connectivity-Preserving Multi-Agent Area Coverage via Optimal-Transport-Based Density-Driven Optimal Control (D2OC)
Connectivity-Preserving Multi-Agent Area Coverage via Optimal-Transport-Based Density-Driven Optimal Control (D2OC) Open
Multi-agent systems play a central role in area coverage tasks across search-and-rescue, environmental monitoring, and precision agriculture. Achieving non-uniform coverage, where spatial priorities vary across the domain, requires coordin…
View article: Connectivity-Preserving Multi-Agent Area Coverage via Optimal-Transport-Based Density-Driven Optimal Control (D2OC)
Connectivity-Preserving Multi-Agent Area Coverage via Optimal-Transport-Based Density-Driven Optimal Control (D2OC) Open
Multi-agent systems play a central role in area coverage tasks across search-and-rescue, environmental monitoring, and precision agriculture. Achieving non-uniform coverage, where spatial priorities vary across the domain, requires coordin…
View article: ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning
ADF-LoRA: Alternating Low-Rank Aggregation for Decentralized Federated Fine-Tuning Open
This paper revisits alternating low-rank updates for federated fine-tuning and examines their behavior in decentralized federated learning (DFL). While alternating the LoRA matrices has been shown to stabilize aggregation in centralized FL…
View article: Mitigating the Effects of Sensor and Actuator Attacks in Uncertain Networked Multiagent Systems
Mitigating the Effects of Sensor and Actuator Attacks in Uncertain Networked Multiagent Systems Open
This paper presents a novel distributed robust adaptive control architecture for leader–follower networked multiagent systems with static undirected communication graph topologies to mitigate the effects of time-varying sensor and actuator…
View article: The Impossibility of Real-Time Central Control: Deriving the Thermodynamic Superiority of Decentralized Hayek-Agents from the Holographic Limits of Computation
The Impossibility of Real-Time Central Control: Deriving the Thermodynamic Superiority of Decentralized Hayek-Agents from the Holographic Limits of Computation Open
The integration of autonomous AI agents into critical infrastructure (Energy Markets, Logistics) poses a choice between centralized optimization and decentralized coordination. This paper applies the SDRIS framework [1-21] to prove that ce…
View article: Enhanced cybersecurity via decentralization AI and Blockchain
Enhanced cybersecurity via decentralization AI and Blockchain Open
As artificial intelligence (AI) becomes ever more prevalent in cyber security, the call for AI systems that are both secure and decentralized grows stronger. In this context, block chain technology stands out as a powerful tool for enhanci…
View article: The Impossibility of Real-Time Central Control: Deriving the Thermodynamic Superiority of Decentralized Hayek-Agents from the Holographic Limits of Computation
The Impossibility of Real-Time Central Control: Deriving the Thermodynamic Superiority of Decentralized Hayek-Agents from the Holographic Limits of Computation Open
The integration of autonomous AI agents into critical infrastructure (Energy Markets, Logistics) poses a choice between centralized optimization and decentralized coordination. This paper applies the SDRIS framework [1-21] to prove that ce…
View article: Decentralized Federated Anomaly Detection in Mobile Networks
Decentralized Federated Anomaly Detection in Mobile Networks Open
Networks face growing challenges such as Distributed Denial-of-Service attacks, malware propagation, unauthorized access, and irregular traffic patterns. Traditional centralized or static anomaly detection methods often struggle with scala…
View article: Multi-Agent Coordination in Autonomous Vehicle Routing: A Simulation-Based Study of Communication, Memory, and Routing Loops
Multi-Agent Coordination in Autonomous Vehicle Routing: A Simulation-Based Study of Communication, Memory, and Routing Loops Open
Multi-agent coordination is critical for next-generation autonomous vehicle (AV) systems, yet naive implementations of communication-based rerouting can lead to catastrophic performance degradation. This study investigates a fundamental pr…
View article: Multi-Agent Coordination in Autonomous Vehicle Routing: A Simulation-Based Study of Communication, Memory, and Routing Loops
Multi-Agent Coordination in Autonomous Vehicle Routing: A Simulation-Based Study of Communication, Memory, and Routing Loops Open
Multi-agent coordination is critical for next-generation autonomous vehicle (AV) systems, yet naive implementations of communication-based rerouting can lead to catastrophic performance degradation. This study investigates a fundamental pr…
View article: Algorithms of mobile agent deployment on a segment under communication delay and network topology switching
Algorithms of mobile agent deployment on a segment under communication delay and network topology switching Open
A group of mobile agents on a straight line is considered. First- and second-order integrators are used as agent models. Decentralized control protocols are proposed that provide both uniform and specified nonlinear uniform (uniform with r…
View article: Systematic Review of Graph Neural Network and Consensus Algorithm-Based Approaches for Proactive Deadlock Detection in Distributed Systems
Systematic Review of Graph Neural Network and Consensus Algorithm-Based Approaches for Proactive Deadlock Detection in Distributed Systems Open
Deadlocks occur when a group of processes wait indefinitely for resources held by others, forming a dependency cycle that halts system progress. In distributed systems, deadlocks are particularly challenging to detect and resolve due to th…
View article: Path Planning through Multi-Agent Reinforcement Learning in Dynamic Environments
Path Planning through Multi-Agent Reinforcement Learning in Dynamic Environments Open
Path planning in dynamic environments is a fundamental challenge in intelligent transportation and robotics, where obstacles and conditions change over time, introducing uncertainty and requiring continuous adaptation. While existing appro…
View article: Symmetry-Breaking in Multi-Agent Navigation: Winding Number-Aware MPC with a Learned Topological Strategy
Symmetry-Breaking in Multi-Agent Navigation: Winding Number-Aware MPC with a Learned Topological Strategy Open
We address the fundamental challenge of resolving symmetry-induced deadlocks in distributed multi-agent navigation by proposing a new hierarchical navigation method. When multiple agents interact, it is inherently difficult for them to aut…