Results 91 to 100 of about 58,229 (203)
Applied Sciences, 2019 With the current advance of technology, agent-based applications are becoming a standard in a great variety of domains such as e-commerce, logistics, supply chain management, telecommunications, healthcare, and manufacturing.
Vicente Julian, Vicente Botti
doaj +1 more source
Discrete Dynamics in Nature and Society, 2019 In this paper, adaptive guaranteed-performance consensus control problems for multiagent systems with an adjustable convergence speed are investigated.
Haiying Ma +3 more
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Rescue Protocols for Canine Non‐Indolent B Cell Lymphoma: A Systematic Review
Veterinary and Comparative Oncology, EarlyView.ABSTRACT Canine lymphoma is a heterogenous group of diseases. The most common subtype is diffuse large B cell lymphoma (DLBCL), though definitive diagnosis beyond non‐indolent = multicentric B cell lymphoma is not often achieved in clinical practice as it requires histopathology. Most dogs respond well to standard‐of‐care multiagent chemotherapy (CHOP)
Claire Marie Cannon, Peter Bennett
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Finite-Time Distributed Energy-to-Peak Control for Uncertain Multiagent Systems
Abstract and Applied Analysis, 2014 This paper investigates the finite-time distributed L2–L∞ consensus control problem of multiagent systems with parameter uncertainties. The relative states of neighboring agents are used to construct the control law and some agents know their own states.
Qu Chenggang +4 more
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a cross-entropy based multiagent approach for multiclass activity chain modeling and simulation [PDF]
This paper attempts to model complex destination-chain, departure time and route choices based on activity plan implementation and proposes an arc-based cross entropy method for solving approximately the dynamic user equilibrium in multiagent-based ...
Jean-Patrick Lebacque, Tai-Yu Ma
core
A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
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Trajectory Modeling by Distributed Gaussian Processes in Multiagent Systems. [PDF]
Sensors (Basel), 2022 Xin D, Shi L.
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Computational Mechanism Design: A Call to Arms
, 2003 Game theory has developed powerful tools for analyzing decision making in systems with multiple autonomous actors. These tools, when tailored to computational settings, provide a foundation for building multiagent software systems.
Dash, Rajdeep K +2 more
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Financial Time Series Uncertainty: A Review of Probabilistic AI Applications
Journal of Economic Surveys, Volume 40, Issue 2, Page 915-953, April 2026.ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen +4 more
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Integral Reinforcement-Learning-Based Optimal Containment Control for Partially Unknown Nonlinear Multiagent Systems. [PDF]
Entropy (Basel), 2023 Wu Q, Wu Y, Wang Y.
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