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A security framework for mobile agent systems
Security is a very important challenge in mobile agent systems due to the strong dependence of agents on the platform and vice versa. According to...
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Multi-agent reinforcement learning behavioral control for nonlinear second-order systems
Reinforcement learning behavioral control (RLBC) is limited to an individual agent without any swarm mission, because it models the behavior priority...
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A comprehensive analysis of agent factorization and learning algorithms in multiagent systems
In multiagent systems, agent factorization denotes the process of segmenting the state-action space of the environment into distinct components, each...
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Modeling and reinforcement learning in partially observable many-agent systems
There is a prevalence of multiagent reinforcement learning (MARL) methods that engage in centralized training. These methods rely on all the agents...
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Event-triggered distributed optimization for model-free multi-agent systems
In this paper, the distributed optimization problem is investigated for a class of general nonlinear model-free multi-agent systems. The dynamical...
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Genetic algorithm-based secure cooperative control for high-order nonlinear multi-agent systems with unknown dynamics
Research has recently grown on multi-agent systems (MAS) and their coordination and secure cooperative control, for example in the field of...
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Learning a data-efficient model for a single agent in homogeneous multi-agent systems
Training Reinforcement Learning (RL) policies for a robot requires an extensive amount of data recorded while interacting with the environment....
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Towards resilient average consensus in multi-agent systems: a detection and compensation approach
Consensus is one of the fundamental distributed control technologies for collaboration in multi-agent systems such as collaborative handling in...
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Event-triggered cooperative robust formation control of multi-agent systems via reinforcement learning
This article develops an event-triggered cooperative robust formation control scheme for nonlinear multi-agent systems with dynamic uncertainties via...
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Quantized Iterative Learning Bipartite Containment Tracking Control for Unknown Nonlinear Multi-agent Systems
This paper proposes a quantized model-free adaptive iterative learning control (MFAILC) algorithm to solve the bipartite containment tracking problem...
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Embedded decision support platform based on multi-agent systems
There has been an outstanding use of memory storage of processors as current applications: Artificial Intelligence-based applications,...
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Imprecise Probabilistic Model Checking for Stochastic Multi-agent Systems
Standard techniques for model checking stochastic multi-agent systems usually assume the transition probabilities describing the system dynamics to...
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Multi-Agent Systems for Collaborative Inference Based on Deep Policy Q-Inference Network
This study tackles the problem of increasing efficiency and scalability in deep neural network (DNN) systems by employing collaborative inference, an...
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Event-triggered consensus control of heterogeneous multi-agent systems: model- and data-based approaches
This article addresses the model- and data-based event-triggered consensus of heterogeneous leader/follower multi-agent systems (MASs). A dynamic...
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Reliability and performance of resource efficiency in dynamic optimization scheduling using multi-agent microservice cloud-fog on IoT applications
In the ever-evolving landscape of technology, both in the Internet of Things (IoT) and of microservice-based cloud-fog with IoT applications,...
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Data-driven cooperative output regulation of multi-agent systems under distributed denial of service attacks
This paper addresses an optimal, cooperative output regulation problem for multi-agent systems with distributed denial of service attacks and unknown...
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Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks
This article examines the prescribed-time sampled-data control problem for multi-agent systems in signed networks. A time-varying high gain-based...
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Influence of Device Performance and Agent Advice on User Trust and Behaviour in a Care-taking Scenario
Monitoring systems have become increasingly prevalent in order to increase the safety of elderly people who live alone. These systems are designed to...
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Competitive Collaboration for Complex Task Learning in Agent Systems
This paper presents a novel competitive collaboration-based reinforcement learning strategy to improve the performance of goal-oriented autonomous...
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Data-driven cooperative optimal output regulation for linear discrete-time multi-agent systems by online distributed adaptive internal model approach
In this study, a data-driven learning algorithm was developed to estimate the optimal distributed cooperative control policy, which solves the...