Longquan Ma¹, Huarong Zhao^1,*, Liqin Zhou¹, Linbo Xie^1,*, Hongnian Yu²

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.075679 - 09 April 2026

Abstract This paper studies a sampling-based dynamic event-triggered fixed-time bipartite formation algorithm for a class of continuous-time multi-agent systems with communication constraints. First, a periodic sampling mechanism is designed to reduce the system’s communication frequency. Then, a dynamic event-triggered control algorithm based on auxiliary variables is developed for sampled-data systems to further reduce the system’s triggering frequency. Next, to enhance the convergence speed of the dynamic event-triggered control method, a dynamic event-triggered fixed-time bipartite formation control scheme is investigated. Finally, using Lyapunov stability theory, signed graph theory, and relevant inequalities, a rigorous theoretical proof of the More >

Xin Yu, Xi Fang^*

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.075607 - 09 April 2026

Abstract This paper addresses the challenging problem of multi-agent dynamic target pursuit under stringent communication constraints (including delays and range limits), where the agile targets are non-cooperative and free from such limitations. To tackle this, we propose CRS-DQN, a novel Deep Q-Network algorithm designed for this scenario. CRS-DQN enables agents to learn effective pursuit strategies through deep reinforcement learning despite partial observability and constrained information sharing. Simulation experiments systematically evaluate the impact of key parameters. The results show that pursuit performance degrades monotonically with increased communication delay. In contrast, the communication radius exhibits a non-linear effect: More >

Go Sato¹, Shusaku Egami^1,2, Yasuyuki Tahara¹, Akihiko Ohsuga¹, Yuichi Sei^1,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.078188 - 12 March 2026

Abstract While Large Language Models (LLMs) possess the capability to perform a wide range of tasks, security attacks known as prompt injection and jailbreaking remain critical challenges. Existing defense approaches addressing this problem face challenges such as the over-refusal of prompts that contain harmful vocabulary but are semantically benign, and the limited accuracy improvement in machine learning-based approaches due to the ease of distinguishing benign prompts in existing datasets. Therefore, we propose a multi-LLM agent framework aimed at achieving both the accurate rejection of harmful prompts and appropriate responses to benign prompts. Distinct from prior studies,… More >

Atef Gharbi¹, Mohamed Ayari², Nasser Albalawi³, Ahmad Alshammari³, Nadhir Ben Halima^4,*, Zeineb Klai³

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075474 - 12 March 2026

Abstract This paper presents Dual Adaptive Neural Topology (Dual ANT), a distributed dual-network meta-adaptive framework that enhances ant-colony-based multi-agent coordination with online introspection, adaptive parameter control, and privacy-preserving interactions. This approach improves standard Ant Colony Optimization (ACO) with two lightweight neural components: a forward network that estimates swarm efficiency in real time and an inverse network that converts these descriptors into parameter adaptations. To preserve the privacy of individual trajectories in shared pheromone maps, we introduce a locally differentially private pheromone update mechanism that adds calibrated noise to each agent’s pheromone deposit while preserving the efficacy More >

Ans D. Alghamdi^*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-35, 2026, DOI:10.32604/cmc.2025.071210 - 09 December 2025

Abstract Multimodal dialogue systems often fail to maintain coherent reasoning over extended conversations and suffer from hallucination due to limited context modeling capabilities. Current approaches struggle with cross-modal alignment, temporal consistency, and robust handling of noisy or incomplete inputs across multiple modalities. We propose MultiAgent-Chain of Thought (CoT), a novel multi-agent chain-of-thought reasoning framework where specialized agents for text, vision, and speech modalities collaboratively construct shared reasoning traces through inter-agent message passing and consensus voting mechanisms. Our architecture incorporates self-reflection modules, conflict resolution protocols, and dynamic rationale alignment to enhance consistency, factual accuracy, and user engagement. More >

Qin Qin¹, Xuan Jiang^1,*, Jinhua Jiang¹, Dongfang Zhao¹, Zimei Tu¹, Zhiwei Shen²

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4849-4867, 2025, DOI:10.32604/cmc.2025.067919 - 23 October 2025

Abstract The effectiveness of industrial character recognition on cast steel is often compromised by factors such as corrosion, surface defects, and low contrast, which hinder the extraction of reliable visual information. The problem is further compounded by the scarcity of large-scale annotated datasets and complex noise patterns in real-world factory environments. This makes conventional OCR techniques and standard deep learning models unreliable. To address these limitations, this study proposes a unified framework that integrates adaptive image preprocessing with collaborative reasoning among LLMs. A Biorthogonal 4.4 (bior4.4) wavelet transform is adaptively tuned using DE to enhance character… More >

Yann-Horng Lin¹, Wen-Jer Chang^1,*, Yi-Chen Lee^2,*, Muhammad Shamrooz Aslam³, Cheung-Chieh Ku⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2231-2262, 2025, DOI:10.32604/cmes.2025.067464 - 31 August 2025

Abstract An Interval Type-2 (IT-2) fuzzy controller design approach is proposed in this research to simultaneously achieve multiple control objectives in Nonlinear Multi-Agent Systems (NMASs), including formation, containment, and collision avoidance. However, inherent nonlinearities and uncertainties present in practical control systems contribute to the challenge of achieving precise control performance. Based on the IT-2 Takagi-Sugeno Fuzzy Model (T-SFM), the fuzzy control approach can offer a more effective solution for NMASs facing uncertainties. Unlike existing control methods for NMASs, the Formation and Containment (F-and-C) control problem with collision avoidance capability under uncertainties based on the IT-2 T-SFM… More >

Taimoor Hassan¹, Ibrar Hussain^1,*, Hafiz Mahfooz Ul Haque², Hamid Turab Mirza³, Muhammad Nadeem Ali⁴, Byung-Seo Kim^4,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 2071-2094, 2025, DOI:10.32604/cmc.2025.068533 - 29 August 2025

Abstract Smart learning environments have been considered as vital sources and essential needs in modern digital education systems. With the rapid proliferation of smart and assistive technologies, smart learning processes have become quite convenient, comfortable, and financially affordable. This shift has led to the emergence of pervasive computing environments, where user’s intelligent behavior is supported by smart gadgets; however, it is becoming more challenging due to inconsistent behavior of Artificial intelligence (AI) assistive technologies in terms of networking issues, slow user responses to technologies and limited computational resources. This paper presents a context-aware predictive reasoning based… More >

Ghulam E Mustafa Abro^1,*, Altaf Mugheri^2,#, Zain Anwar Ali^3,#

Revue Internationale de Géomatique, Vol.34, pp. 301-331, 2025, DOI:10.32604/rig.2025.065595 - 05 June 2025

Abstract Swarm intelligence, derived from the collective behaviour of biological entities, is a novel methodology for overseeing satellite constellations within decentralized control systems. Conventional centralized control systems in satellite constellations encounter constraints in scalability, resilience, and fault tolerance, particularly in extensive constellations. This research examines the use of swarm-based multi-agent systems and distributed algorithms for efficient communication, collision avoidance, and collaborative task execution in satellite constellations. We provide a comprehensive study of current swarm control algorithms, their relevance to satellite systems, and identify areas requiring further research. Principal subjects encompass decentralized decision-making, self-organization, adaptive communication protocols, More >

Aamir Farooq¹, Zhengrong Xiang^1,*, Wen-Jer Chang^2,*, Muhammad Shamrooz Aslam³

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3623-3674, 2025, DOI:10.32604/cmc.2025.063665 - 19 May 2025

Abstract Formation control in multi-agent systems has become a critical area of interest due to its wide-ranging applications in robotics, autonomous transportation, and surveillance. While various studies have explored distributed cooperative control, this review focuses on the theoretical foundations and recent developments in formation control strategies. The paper categorizes and analyzes key formation types, including formation maintenance, group or cluster formation, bipartite formations, event-triggered formations, finite-time convergence, and constrained formations. A significant portion of the review addresses formation control under constrained dynamics, presenting both model-based and model-free approaches that consider practical limitations such as actuator bounds,… More >