Multi-agent Research Articles

Distributed Practical Fixed-Time Resource Allocation Algorithm for Disturbed Multiagent Systems: An Integrated Framework.

The practical fixed-time resource allocation problem is investigated for multi-input-multi-output nonlinear uncertain multiagent systems with disturbed dynamics, subject to global equality and local inequality constraints. Due to the coexistence of distributed high-order dynamics system within agents and decision-making constraints, decision variables in resource allocation optimization problems cannot be directly obtained from the system. Existing strategies are insufficient to solve such complex fixed-time optimization control problems with coupled decision-making constraints. To address these challenges, a novel integrated framework is proposed, fusing symbolic-function-based fixed-time control theory with gradient consistency. The proposed algorithm is implemented through an output-feedback backstepping design process, which involves two stages. First, in the output-feedback design stage, a fixed-time high-order extended state observer estimates the uncertain dynamics and disturbances. Second, in the backstepping design stage, a time-switching controller is developed. This controller's virtual control law has two components: the first employs the proportional-integral control method to satisfy the equality constraints, while the second uses gradient information from the $\epsilon $ -exact penalty function to address the inequality constraints. Using the Lyapunov stability criterion, the proposed algorithm can ensure that all signals remain practical fixed-time stable, and that the error between the outputs of all agents and the optimal solution is maintained within a neighborhood of the origin. Finally, simulations are presented to demonstrate the effectiveness of the approach.

Black patients with cutaneous T-cell lymphoma (CTCL) and their likelihood to receive novel agents: A retrospective cohort analysis.

e13822 Background: Black patients with cutaneous T-cell lymphoma (CTCL) have increased risk of mortality compared to other racial groups. The introduction of novel therapies such as mogamulizumab and brentuximab vedotin (BV) for the treatment of CTCL have demonstrated improved survival compared to standard therapies. We investigated treatment patterns including receipt of novel agents among patients with CTCL to better understand the role of treatment selection as a potential driver of racial disparities. Methods: We performed a retrospective review of 315 patients with a histopathologic diagnosis of mycosis fungoides (MF), Sezary syndrome (SS), or CTCL not otherwise specified (NOS) seen at the Winship Cancer Institute of Emory University from 2000-2023. Clinical data was collected from the electronic medical record and included demographics, histopathologic findings, treatments received, highest disease stage reached, and survival. Systemic therapies were divided into three groups: standard chemotherapy (single agent or multi agent), biologics (interferon, retinoids, extracorporeal photopheresis, and oral methotrexate), and novel agents (mogamulizumab, BV, and clinical trials). The association between overall survival (OS) and race, stage, and treatment category was assessed using univariate and multivariable analysis for significant factors and patients were matched according to age and stage. Results: The cohort was comprised 53.6% of patients identifying as Black (n = 169) and 46.4% white (n = 146). Males made up 57.8% (n = 182) of the cohort and females 42.2% (n = 133). Median age at diagnosis was 59.5 years (range, 12-91). Black patients had an earlier age of diagnosis compared to white (median 50 years vs. 63, p < 0.001). The majority of patients had a pathological diagnosis of MF (n = 246, 78.1%), followed by 18.1% SS (n = 57) and 3.8% CTCL NOS (n = 12). Insurance status included private in 50.3% of patients (n = 157), 38.1% Medicaid/Medicare (n = 119), 4.8% uninsured (n = 15) and 6.7% other (n = 21). 53.4% of patients had advanced-stage disease of 2b or higher at time of diagnosis. In the unmatched cohort, Black patients were more likely to receive novel agents compared to white patients (30.8% vs. 19.2%, p = 0.018). However, after matching by age and disease stage, black patients were less likely to receive novel agents (p = 0.019). There were no significant differences in the receipt of biologics or chemotherapy agents. Patients with advanced stage disease had improved OS if they received novel agents (HR 0.39, 0.24-0.65, p < 0.001). Conclusions: Receipt of novel agents was associated with improved survival. Black patients were less likely to receive novel agents when matched for age and disease stage. These findings suggest that treatment patterns, such as the receipt of novel agents, could play a role in the racial differences in clinical outcomes in CTCL.

Predefined-Time Consensus of Multiagent System: Nonchattering Scheme.

This article investigates the global predefined-time consensus (PTC) of multiagent system (MAS) via constructing a duplex communication network. Unlike the traditional finite-/fixed-time convergence, our method allows the upper-bound of settling-time to be an explicit constant, which is tunable and can be set beforehand without relating with the network information, controlling parameters, and initial conditions. In particular, our approach uses a smooth, nonchattering consensus scheme that avoids conventional discontinuous functions like signum and absolute value functions. By the Lyapunov stability analysis, the sufficient criterion is deduced for ensuring the PTC of MAS. Finally, simulations confirm the effectiveness of our proposed nonchattering scheme.

Constraining an Unconstrained Multi-agent Policy with offline data.

Constraining an Unconstrained Multi-agent Policy with offline data.

Self-adaptive production scheduling for discrete manufacturing workshop using multi-agent cyber physical system

Self-adaptive production scheduling for discrete manufacturing workshop using multi-agent cyber physical system

Data-driven-based fully distributed event-triggered control for nonlinear multi-agent systems

Data-driven-based fully distributed event-triggered control for nonlinear multi-agent systems

Cooperative spheroidal coverage control of multi-agent systems in 3D non-convex environments

Cooperative spheroidal coverage control of multi-agent systems in 3D non-convex environments

Observer-Based Double Event-Triggered Fast Finite-Time Consensus Control for Heterogeneous Nonlinear Multi-Agent Systems

Observer-Based Double Event-Triggered Fast Finite-Time Consensus Control for Heterogeneous Nonlinear Multi-Agent Systems

Adaptive observer-based bipartite tracking consensus for nonlinear multi-agent systems with unknown sensor failures.

Adaptive observer-based bipartite tracking consensus for nonlinear multi-agent systems with unknown sensor failures.

Rigidity-based formation control with prescribed performance for second-order multi-agents system

Rigidity-based formation control with prescribed performance for second-order multi-agents system

Debugging in the Domain-Specific Modeling Languages for multi-agent systems

Debugging in the Domain-Specific Modeling Languages for multi-agent systems

Distributed Optimal Consensus Problem of Input Constrained Nonlinear Discrete-Time MASs: A Mode-Free Reinforcement Learning Approach.

In this article, a model-free reinforcement learning (RL) approach is proposed for solving the optimal consensus control issue of nonlinear discrete-time multiagent systems with input constraint. To address the challenge of solving the coupled discrete Hamilton-Jacobi-Bellman (HJB) equation, a RL approach based on actor-critic framework is proposed for optimal consensus control. A well-defined cost function is designed, and the actor and critic networks are updated through online learning to obtain the optimal controllers. Furthermore, the actuator's performance is often limited due to physical constraints. To address such actuator constraints, a gradual transition control (GTC) method is proposed, and update-free and update-weak policies are introduced to further optimize network performance. Additionally, in real-world distributed systems, the actor-critic networks deployed in each agent rely on data from neighboring agents, which necessitates addressing the issue of distributed synchronization. To address this challenge, the synchronization blocking method is designed, which designs additional control signals for each agent to handle these issues. Finally, two simulations under different scenarios are presented to verify the effectiveness of the proposed approach.

Consensus of multi-agent systems under binary-valued measurements: An event-triggered coordination approach

Consensus of multi-agent systems under binary-valued measurements: An event-triggered coordination approach

Encoding–decoding-based distributed event-triggered sliding mode consensus control for multiagent systems under constrained bit rate

Encoding–decoding-based distributed event-triggered sliding mode consensus control for multiagent systems under constrained bit rate

Bilateral Cooperative Control of Nonlinear Multiagent Systems With State and Output Quantification.

The fuzzy adaptive state and output quantization bilateral cooperative control problem for nonlinear multiagent systems (NMASs) is studied. Since the considered system is nonlinear, fuzzy logic system (FLS) is applied to approximate the unknown nonlinear function, and a fuzzy state observer is constructed because the state cannot be measured. A second-order command filter is used to solve the complex problem of calculating the time derivative of the virtual control function, and a uniform quantizer is used for fuzzy adaptive inversion design in the process of controller design. Ultimately, the effectiveness of the proposed control method is verified by a series of simulation experiments and research results.

Second-order consensus of matrix-weighted switched multiagent systems

Second-order consensus of matrix-weighted switched multiagent systems

Disturbance observer-based adaptive fuzzy finite-time cooperative control for high-order multi-agent systems with input saturation

Disturbance observer-based adaptive fuzzy finite-time cooperative control for high-order multi-agent systems with input saturation

Prescribed-time fault-tolerant consensus for uncertain nonlinear multi-agent systems

Prescribed-time fault-tolerant consensus for uncertain nonlinear multi-agent systems

Data-driven bipartite synchronization control of multi-agent systems with asymmetric input saturation over switching networks

Data-driven bipartite synchronization control of multi-agent systems with asymmetric input saturation over switching networks

Distributed data-driven iterative learning consensus tracking for unknown multi-agent systems using evolutionary neural networks

Distributed data-driven iterative learning consensus tracking for unknown multi-agent systems using evolutionary neural networks