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Articles de revues sur le sujet « Multi-agent paradigms »

Auteur : Grafiati

Publié le 10 mars 2023

Mis à jour le 31 juillet 2025

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1

Patel, Rakesh B., and Satish K. Shah. "Multi-agent controller using soft computational paradigms." Indian Journal of Applied Research 3, no. 2 (2011): 138–41. http://dx.doi.org/10.15373/2249555x/feb2013/48.

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HORLING, BRYAN, and VICTOR LESSER. "A survey of multi-agent organizational paradigms." Knowledge Engineering Review 19, no. 4 (2004): 281–316. http://dx.doi.org/10.1017/s0269888905000317.

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Many researchers have demonstrated that the organizational design employed by an agent system can have a significant, quantitative effect on its performance characteristics. A range of organizational strategies have emerged from this line of research, each with different strengths and weaknesses. In this article we present a survey of the major organizational paradigms used in multi-agent systems. These include hierarchies, holarchies, coalitions, teams, congregations, societies, federations, markets, and matrix organizations. We will provide a description of each, discuss their advantages and

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Li, Mengxian, Qi Wang, and Yongjun Xu. "GTDE: Grouped Training with Decentralized Execution for Multi-agent Actor-Critic." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 17 (2025): 18368–76. https://doi.org/10.1609/aaai.v39i17.34021.

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The rapid advancement of multi-agent reinforcement learning (MARL) has given rise to diverse training paradigms to learn the policies of each agent in the multi-agent system. The paradigms of decentralized training and execution (DTDE) and centralized training with decentralized execution (CTDE) have been proposed and widely applied. However, as the number of agents increases, the inherent limitations of these frameworks significantly degrade the performance metrics, such as win rate, total reward, etc. To reduce the influence of the increasing number of agents on the performance metrics, we p

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Baykasoglu, Adil, Vahit Kaplanoglu, Rizvan Erol, and Cenk Sahin. "A MULTI-AGENT FRAMEWORK FOR LOAD CONSOLIDATION IN LOGISTICS." TRANSPORT 26, no. 3 (2011): 320–28. http://dx.doi.org/10.3846/16484142.2011.622141.

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Logistics companies mainly provide land transportation services facing with difficulties in making effective operational decisions. This is especially the case of making load/capacity/route planning and load consolidation where customer orders are generally unpredictable and subject to sudden changes. Classical modelling and decision support systems are mostly insufficient for providing satisfactory solutions in a reasonable time solving such dynamic problems. Agent-based approaches, especially multi-agent paradigms that can be considered as relatively new members of system science and softwar

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Menassel, Yahia, Toufik Marir, and Farid Mokhati. "Operational profile development methodology for normative multi-agent systems." Multiagent and Grid Systems 19, no. 1 (2023): 1–22. http://dx.doi.org/10.3233/mgs-221507.

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Software reliability refers to the ability of a system to perform its intended function under specified conditions for a specified period of time. The first critical step in the software reliability testing process is to create a Software Operational Profile (SOP). Several methodologies for creating SOP have been proposed. Nonetheless, nearly all the proposed studies have neglected the uniqueness of the new software paradigms, despite the fact that these are generally distinguished by their own concepts and methodologies. One of these software paradigms is multi-agent systems. Rather than usin

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Mitra, Aritra. "Towards Robust Multi-Agent Reinforcement Learning." Proceedings of the AAAI Symposium Series 3, no. 1 (2024): 308. http://dx.doi.org/10.1609/aaaiss.v3i1.31222.

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Stochastic gradient descent (SGD) is at the heart of large-scale distributed machine learning paradigms such as federated learning (FL). In these applications, the task of training high-dimensional weight vectors is distributed among several workers that exchange information over networks of limited bandwidth. While parallelization at such an immense scale helps to reduce the computational burden, it creates several other challenges: delays, asynchrony, and most importantly, a significant communication bottleneck. The popularity and success of SGD can be attributed in no small part to the fact

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Li, Haiyang, Ping Yang, Weidong Liu, Shaoqiang Yan, Xinyi Zhang, and Donglin Zhu. "Multi-Agent Reinforcement Learning in Games: Research and Applications." Biomimetics 10, no. 6 (2025): 375. https://doi.org/10.3390/biomimetics10060375.

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Biological systems, ranging from ant colonies to neural ecosystems, exhibit remarkable self-organizing intelligence. Inspired by these phenomena, this study investigates how bio-inspired computing principles can bridge game-theoretic rationality and multi-agent adaptability. This study systematically reviews the convergence of multi-agent reinforcement learning (MARL) and game theory, elucidating the innovative potential of this integrated paradigm for collective intelligent decision-making in dynamic open environments. Building upon stochastic game and extensive-form game-theoretic frameworks

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Surynek, Pavel. "Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 14 (2021): 12409–17. http://dx.doi.org/10.1609/aaai.v35i14.17472.

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We introduce multi-goal multi agent path finding (MG-MAPF) which generalizes the standard discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate agents in an undirected graph from their starting vertices to one individual goal vertex per agent, MG-MAPF assigns each agent multiple goal vertices and the task is to visit each of them at least once. Solving MG-MAPF not only requires finding collision free paths for individual agents but also determining the order of visiting agent's goal vertices so that common objectives like the sum-of-costs are optimized. We sug

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DARBYSHIRE, PAUL. "EFFECTS OF COMMUNICATION ON GROUP LEARNING RATES IN A MULTI-AGENT ENVIRONMENT." Advances in Complex Systems 06, no. 03 (2003): 405–26. http://dx.doi.org/10.1142/s0219525903000979.

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Distillations utilize multi-agent based modeling and simulation techniques to study warfare as a complex adaptive system at the conceptual level. The focus is placed on the interactions between the agents to facilitate study of cause and effect between individual interactions and overall system behavior. Current distillations do not utilize machine-learning techniques to model the cognitive abilities of individual combatants but employ agent control paradigms to represent agents as highly instinctual entities. For a team of agents implementing a reinforcement-learning paradigm, the rate of lea

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Tokadlı, Güliz, Kaitlyn Ouverson, Chase Meusel, Austin Garcia, Stephen B. Gilbert, and Michael C. Dorneich. "An Analysis of Video Games Using the Dimensions of Human-Agent Interaction." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 716–20. http://dx.doi.org/10.1177/1541931218621163.

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Designers of human-agent interaction techniques may benefit from an analysis of existing video games that include aspects of human-agent teaming. Many popular multi-player video games have been designed to integrate multiple human and computer agents in pursuit of a common objective and can serve as a testbed to explore novel interaction methods in human-agent teams. A guiding framework of human-agent interaction was created to bridge best practices between video game and real-world domains. The framework was used to analyze games on five main dimensions: 1) Levels of Automation, 2) Levels of

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Carneiro, Tiago, Pedro Andrade, Gilberto Camara, Miguel Monteiro, and Rodrigo Pereira. "An extensible toolbox for modeling nature–society interactions." Environmental Modelling & Software 46, August 2013 (2013): 104–17. https://doi.org/10.1016/j.envsoft.2013.03.002.

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Modeling interactions between social and natural systems is a hard task. It involves collecting data, building up a conceptual approach, implementing, calibrating, simulating, validating, and possibly repeating these steps again and again. There are different conceptual approaches proposed in the literature to tackle this problem. However, for complex problems it is better to combine different approaches, giving rise to a need for flexible and extensible frameworks for modeling nature–society interactions. In this paper we present TerraME, an open source toolbox that supports multi-parad

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Ygge, F., and H. Akkermans. "Decentralized Markets versus Central Control: A Comparative Study." Journal of Artificial Intelligence Research 11 (October 1, 1999): 301–33. http://dx.doi.org/10.1613/jair.627.

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Multi-Agent Systems (MAS) promise to offer solutions to problems where established, older paradigms fall short. In order to validate such claims that are repeatedly made in software agent publications, empirical in-depth studies of advantages and weaknesses of multi-agent solutions versus conventional ones in practical applications are needed. Climate control in large buildings is one application area where multi-agent systems, and market-oriented programming in particular, have been reported to be very successful, although central control solutions are still the standard practice. We have the

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DE GRANDE, PABLO, and MANUEL EGUIA. "STRATEGY SPACE EXPLORATION OF A MULTI-AGENT MODEL FOR THE LABOR MARKET." International Journal of Modern Physics C 17, no. 03 (2006): 357–71. http://dx.doi.org/10.1142/s0129183106008534.

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We present a multi-agent system where typical labor market mechanisms emerge. Based on a few simple rules, our model allows for different interpretative paradigms to be represented and for different scenarios to be tried out. We thoroughly explore the space of possible strategies both for those unemployed and for companies and analyze the trade-off between these strategies regarding global social and economical indicators.

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Dosi, G., M. C. Pereira, A. Roventini, and M. E. Virgillito. "Technological paradigms, labour creation and destruction in a multi-sector agent-based model." Research Policy 51, no. 10 (2022): 104565. http://dx.doi.org/10.1016/j.respol.2022.104565.

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Yang, Shuo, Xinjun Mao, Sen Yang, and Zhe Liu. "Towards a hybrid software architecture and multi-agent approach for autonomous robot software." International Journal of Advanced Robotic Systems 14, no. 4 (2017): 172988141771608. http://dx.doi.org/10.1177/1729881417716088.

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To support robust plan execution of autonomous robots in dynamic environments, autonomous robot software should include adaptive and reactive capabilities to cope with the dynamics and uncertainties of the evolving states of real-world environments. However, conventional software architectures such as sense-model-plan-act and behaviour-based paradigms are inadequate for meeting the requirements. A lack of sensing during acting in the sense-model-plan-act paradigm makes the software slow to react to run-time contingencies, whereas the behaviour-based architectures typically fall short in planni

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Jaswal, Shivani, and Manisha Malhotra. "MATEM." International Journal of Cloud Applications and Computing 12, no. 1 (2022): 1–17. http://dx.doi.org/10.4018/ijcac.305213.

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The paradigms of Cloud Computing have risen at a very rapid rate. The Cloud Computing demands that a trustworthy or reliable service should be availed by its potential user. However, it is always a challenge for any cloud user to look for service that is suitable as well as reliable in every aspect. For a trustworthy discovery and delivery of cloud services, a multi-layered model i.e., Multi Agent based Trust Evaluation Model (MATEM) has been proposed. It is a multi-agent trust model that will make use of multiple agents to perform and evaluate the credibility of trust through trust evaluation

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Aleksiyev, Oleg, Volodymyr Aleksiyev, and Serhii Neronov. "Multi-agents in transport process control." Bulletin of Kharkov National Automobile and Highway University, no. 100 (April 7, 2023): 15. http://dx.doi.org/10.30977/bul.2219-5548.2023.100.0.15.

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Abstract. Problem The problem is computer science, car transfer, road maintenance, synergy, principles and paradigms of using car computer systems - ACS. The use of multi-agent systems in the virtual management of the transport process allows improving the quality of transport management. A multi-agent system is a collection of interacting agents that can work together to achieve a common goal. Multi-agent systems can be used for better management of logistics processes, in particular in the field of transport. The role of agents in decision-making, including in real time, is considered, which

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Moummadi, Kamal, Rachida Abidar, and Hicham Medromi. "Distributed Resource Allocation." International Journal of Mobile Computing and Multimedia Communications 4, no. 2 (2012): 49–62. http://dx.doi.org/10.4018/jmcmc.2012040104.

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The growth of technological capabilities of mobile devices, the evolution of wireless communication technologies, and the maturity of embedded systems contributed to expand the Machine to machine (M2M) concept. M2M refers to data communication between machines without human intervention. The objective of this paper is to present the grand schemes of a model to be used in an agricultural Decision support System. The authors start by explaining and justifying the need for a hybrid system that uses both Multi-Agent System (MAS) and Constraint Programming (CP) paradigms. Then, the authors propose

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Petrich, Adam M., Joseph A. Sparano, and Samir Parekh. "Paradigms and Controversies in the Treatment of HIV-Related Burkitt Lymphoma." Advances in Hematology 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/403648.

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Burkitt lymphoma (BL) is a very aggressive subtype of non-Hodgkin's lymphoma that occurs with higher frequency in patients with HIV/AIDS. Patients with HIV-related BL (HIV-BL) are usually treated with high-intensity, multi-agent chemotherapy regimens. The addition of the monoclonal antibody Rituximab to chemotherapy has also been studied in this setting. The potential risks and benefits of commonly used regimens are reviewed herein, along with a discussion of controversial issues in the practical management of HIV-BL, including concurrent anti-retroviral therapy, treatment of relapsed and/or r

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Sarratt, Trevor. "Leveraging Communication for Player Modeling and Cooperative Play." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 10, no. 6 (2021): 14–17. http://dx.doi.org/10.1609/aiide.v10i6.12695.

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Collaboration between agents and players within games is a ripe area for exploration. As with adversarial AI, collaborative agents are challenged to accurately model players and adapt their behavior accordingly. The task of cooperation, however, allows for communication between teammates that can prove beneficial in coordinating joint actions and plans. Furthermore, we propose extending established multi-agent communication paradigms to include transfer of information pertinent to player models. By querying goal and preference information from a player, an agent can reduce uncertainty in coord

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González-Briones, Alfonso, Fernando De La Prieta, Mohd Mohamad, Sigeru Omatu, and Juan Corchado. "Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review." Energies 11, no. 8 (2018): 1928. http://dx.doi.org/10.3390/en11081928.

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This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and their application to energy optimization problems. This methodology and related tools have contributed to changes in various paradigms used in energy optimization. Behavior and interactions between agents are key elements that must be understood in order to model energy optimization solutions that are robust, scalable and context-aware. The concept of MAS is introduced in this paper and it is compared with traditional approaches in the development of energy optimization solutions. The different types of ag

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Ovalle Carranza, Demetrio Arturo, Jovani Alberto Jiménez Builes, and César Alberto Collazos Ordóñez. "Model for supporting awareness in the CSCL ALLEGRO environment through a blackboard architecture." Ingeniería e Investigación 26, no. 3 (2006): 67–77. http://dx.doi.org/10.15446/ing.investig.v26n3.14753.

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This paper is aimed at describing collaborative activities, the awareness process and blackboard architecture used within the ALLEGRO system, a multi-agent learning and teaching environment which has included artificial intelligence mechanisms (instructional planning (IP), cased-based reasoning (CBR), multi-agent systems (MAS), intelligent tutoring systems (ITS) and computer supported collaborative learning (CSCL)). The proposed model of awareness promotes communication, collaboration and coordination in CSCL ALLEGRO. MAS-CommonKADS methodology was applied for building the Multi-Agent system.

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Mendoza, E., J. Andramuño, J. Núñez, and L. Córdova. "Intelligent multi-agent architecture for a supervisor of a water treatment plant." Journal of Physics: Conference Series 2090, no. 1 (2021): 012124. http://dx.doi.org/10.1088/1742-6596/2090/1/012124.

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Abstract The rapid development of Information and Communication Technologies (ICT) and high-capacity hardware components make it necessary to achieve a strong integration of automatic systems based on new paradigms on intelligent distributed architectures, where require highly complex supervision and control tasks, due to the generated requirements of the new production systems, the high number of variables to control and the advancement of technologies, especially in industries where continuous processes have been established. In the present work, a distributed hierarchical modular architectu

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Algarvio, Hugo. "Management of Local Citizen Energy Communities and Bilateral Contracting in Multi-Agent Electricity Markets." Smart Cities 4, no. 4 (2021): 1437–53. http://dx.doi.org/10.3390/smartcities4040076.

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Over the last few decades, the electricity sector has experienced several changes, resulting in different electricity markets (EMs) models and paradigms. In particular, liberalization has led to the establishment of a wholesale market for electricity generation and a retail market for electricity retailing. In competitive EMs, customers can do the following: freely choose their electricity suppliers; invest in variable renewable energy such as solar photovoltaic; become prosumers; or form local alliances such as Citizen Energy Communities (CECs). Trading of electricity can be done in spot and

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Yeshchenko, Mykola. "Modeling Blockchain Technology." NaUKMA Research Papers. Computer Science 7 (May 12, 2025): 51–57. https://doi.org/10.18523/2617-3808.2024.7.51-57.

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Blockchain is a very attractive technology because it provides a public, append-only, immutable, and ordered transaction log. Blockchain systems are inherently interdisciplinary as they combine different fields such as cryptography, multi-agent systems, distributed systems, social systems, economics, and finance. Additionally, they have a highly active and dynamic ecosystem where new blockchain platforms and algorithms are constantly being developed due to public and industry interest in the technology. Given the complexity and multifaceted nature of the blockchain, its presentation – modeling

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Makarov, Oleg N., and Elvira B. Abduryakhimova. "MODERN TRANSPORTATION MULTI-AGENT SYSTEMS: IMPACT ON CULTURAL CAPITAL, ECONOMY AND DIGITAL TRANSFORMATION." Krasnoyarsk Science 13, no. 2 (2024): 55–71. http://dx.doi.org/10.12731/2070-7568-2024-13-2-246.

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Multi-agent transport systems represent a convergence of diverse technologies, with the Internet of Things (IoT) serving as a foundational enabler for data orchestration. IoT facilitates seamless integration across networks, devices, and infrastructure, heralding an era where connectivity transcends human-human interactions to encompass interactions between objects and systems. Within IoT-enabled transport ecosystems, physical components become sentient through embedded sensors, perpetually generating vast data streams capturing real-world dynamics. This data deluge holds profound potential fo

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d'AVILA GARCEZ, ARTUR S., LUÍS C. LAMB, KRYSIA BRODA, and DOV M. GABBAY. "APPLYING CONNECTIONIST MODAL LOGICS TO DISTRIBUTED KNOWLEDGE REPRESENTATION PROBLEMS." International Journal on Artificial Intelligence Tools 13, no. 01 (2004): 115–39. http://dx.doi.org/10.1142/s0218213004001442.

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Neural-Symbolic Systems concern the integration of the symbolic and connectionist paradigms of Artificial Intelligence. Distributed knowledge representation is traditionally seen under a symbolic perspective. In this paper, we show how neural networks can represent distributed symbolic knowledge, acting as multi-agent systems with learning capability (a key feature of neural networks). We apply the framework of Connectionist Modal Logics to well-known testbeds for distributed knowledge representation formalisms, namely the muddy children and the wise men puzzles. Finally, we sketch a full solu

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Zheng, Yanling, Siyu Liu, and Jie Zhong. "A Prescribed-Time Consensus Algorithm for Distributed Time-Varying Optimization Based on Multiagent Systems." Mathematics 13, no. 13 (2025): 2190. https://doi.org/10.3390/math13132190.

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This paper presents a distributed optimization algorithm for time-varying objective functions utilizing a prescribed-time convergent multi-agent system within undirected communication networks. Departing from conventional time-invariant optimization paradigms with static optimal solutions, our approach specifically addresses the challenge of tracking dynamic optimal trajectories in evolving environments. A novel continuous-time distributed optimization algorithm is developed based on prescribed-time consensus, guaranteeing the consensus attainment among agents within a user-defined timeframe w

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Dibley, Michael, Haijiang Li, Yacine Rezgui, and John Miles. "AN INTEGRATED FRAMEWORK UTILISING SOFTWARE AGENT REASONING AND ONTOLOGY MODELS FOR SENSOR BASED BUILDING MONITORING." Journal of Civil Engineering and Management 21, no. 3 (2015): 356–75. http://dx.doi.org/10.3846/13923730.2014.890645.

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Smart building monitoring demands a new software infrastructure that can elaborate building domain knowledge in order to provide advanced and intelligent functionalities. Conventional facility management (FM) software tools lack semantically rich components, and that limits the capability of supporting software for automatic information sharing, resource negotiation and to assist in timely decision making. Recent hardware innovation on compact ZigBee sensor devices, software developments on ontology and intelligent software agent paradigms provide a good opportunity to develop tools that can f

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Liu, Yongwen, Dongqing Liu, and Shaolin Zhu. "Bilingual–Visual Consistency for Multimodal Neural Machine Translation." Mathematics 12, no. 15 (2024): 2361. http://dx.doi.org/10.3390/math12152361.

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Current multimodal neural machine translation (MNMT) approaches primarily focus on ensuring consistency between visual annotations and the source language, often overlooking the broader aspect of multimodal coherence, including target–visual and bilingual–visual alignment. In this paper, we propose a novel approach that effectively leverages target–visual consistency (TVC) and bilingual–visual consistency (BiVC) to improve MNMT performance. Our method leverages visual annotations depicting concepts across bilingual parallel sentences to enhance multimodal coherence in translation. We exploit t

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González-Cancelas, Nicoletta, Javier Vaca-Cabrero, and Alberto Camarero-Orive. "Multi-Agent System for Smart Roll-on/Roll-off Terminal Management: Orchestration and Communication Strategies for AI-Driven Optimization." Applied Sciences 15, no. 11 (2025): 6079. https://doi.org/10.3390/app15116079.

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This study presents a structured multi-agent system (MAS) architecture aimed at optimizing operational efficiency in roll-on/roll-off (Ro-Ro) terminal management through intelligent coordination and decentralized decision-making. The proposed framework enhances space allocation, route planning, traffic control, and boarding coordination, enabling real-time decision-making and adaptive operational strategies. Through structured MAS architecture, agents interact dynamically to optimize vehicle flow, reducing congestion and improving overall efficiency. The study evaluates the system’s potential

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Casadei, Roberto, Gianluca Aguzzi, and Mirko Viroli. "A Programming Approach to Collective Autonomy." Journal of Sensor and Actuator Networks 10, no. 2 (2021): 27. http://dx.doi.org/10.3390/jsan10020027.

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Research and technology developments on autonomous agents and autonomic computing promote a vision of artificial systems that are able to resiliently manage themselves and autonomously deal with issues at runtime in dynamic environments. Indeed, autonomy can be leveraged to unburden humans from mundane tasks (cf. driving and autonomous vehicles), from the risk of operating in unknown or perilous environments (cf. rescue scenarios), or to support timely decision-making in complex settings (cf. data-centre operations). Beyond the results that individual autonomous agents can carry out, a further

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Pantazis, Evangelos, and David Gerber. "A framework for generating and evaluating façade designs using a multi-agent system approach." International Journal of Architectural Computing 16, no. 4 (2018): 248–70. http://dx.doi.org/10.1177/1478077118805874.

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Digital design paradigms in architecture have been rooted in representational models which are geometry centered and therefore fail to capture building complexity holistically. Due to a lack of computational design methodologies, existing digital design workflows do little in predicting design performance in the early design stage and in most cases analysis and design optimization are done after a design is fixed. This work proposes a new computational design methodology, intended for use in the area of conceptual design of building design. The proposed methodology is implemented into a multi-

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Bertoli, Annalisa, Andrea Cervo, Carlo Alberto Rosati, and Cesare Fantuzzi. "Smart Node Networks Orchestration: A New E2E Approach for Analysis and Design for Agile 4.0 Implementation." Sensors 21, no. 5 (2021): 1624. http://dx.doi.org/10.3390/s21051624.

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The field of cyber-physical systems is a growing IT research area that addresses the deep integration of computing, communication and process control, possibly with humans in the loop. The goal of such area is to define modelling, controlling and programming methodologies for designing and managing complex mechatronics systems, also called industrial agents. Our research topic mainly focuses on the area of data mining and analysis by means of multi-agent orchestration of intelligent sensor nodes using internet protocols, providing also web-based HMI visualizations for data interpretability and

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Gurpreet Singh Panesar, Et al. "A Hybrid Optimization Algorithm for Efficient Virtual Machine Migration and Task Scheduling Using a Cloud-Based Adaptive Multi-Agent Deep Deterministic Policy Gradient Technique." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 742–56. http://dx.doi.org/10.17762/ijritcc.v11i10.8570.

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This To achieve optimal system performance in the quickly developing field of cloud computing, efficient resource management—which includes accurate job scheduling and optimized Virtual Machine (VM) migration—is essential. The Adaptive Multi-Agent System with Deep Deterministic Policy Gradient (AMS-DDPG) Algorithm is used in this study to propose a cutting-edge hybrid optimization algorithm for effective virtual machine migration and task scheduling. An sophisticated combination of the War Strategy Optimization (WSO) and Rat Swarm Optimizer (RSO) algorithms, the Iterative Concept of War and Ra

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Narayanasamy, Iswarya, and Venkateswari Rajamanickam. "A Cascaded Multi-Agent Reinforcement Learning-Based Resource Allocation for Cellular-V2X Vehicular Platooning Networks." Sensors 24, no. 17 (2024): 5658. http://dx.doi.org/10.3390/s24175658.

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The platooning of cars and trucks is a pertinent approach for autonomous driving due to the effective utilization of roadways. The decreased gas consumption levels are an added merit owing to sustainability. Conventional platooning depended on Dedicated Short-Range Communication (DSRC)-based vehicle-to-vehicle communications. The computations were executed by the platoon members with their constrained capabilities. The advent of 5G has favored Intelligent Transportation Systems (ITS) to adopt Multi-access Edge Computing (MEC) in platooning paradigms by offloading the computational tasks to the

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Sokolovska, Zoia. "Hybrid Simulation Models in Management Decision Support Processes." Economics: time realities 3, no. 79 (2025): 120–31. https://doi.org/10.15276/etr.03.2025.12.

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The article presents hybrid simulation modeling as an analytical basis for supporting managerial decision-making. The main concepts of building hybrid simulation models and the features of their architecture are considered. The expediency of using models of this class in the study of complex economic systems is proved. A hybrid model of production and sales activities of a pharmaceutical enterprise, built on the basis of a combination of three simulation paradigms – discrete-event, agent-based and system dynamics – on the software platform of the AnyLogic multi-approach simulation modeling sys

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Meng, Fanfei, Lalita Jagadeesan, and Marina Thottan. "Model-based reinforcement learning for service mesh fault resiliency in a web application-level." Applied and Computational Engineering 43, no. 1 (2024): 115–27. http://dx.doi.org/10.54254/2755-2721/43/20230817.

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Microservice-based architectures enable different aspects of applications to be created and updated independently, even after deployment. Associated technologies such as service mesh provide fault resiliency through attribute configurations that govern self-adaptive application-level behavior in response to failures, in a manner transparent to the application and constituent microservices. While this provides tremendous flexibility, the configured values of these attributes and the relationships among them can significantly affect the performance and fault resilience of the overall application

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Hu, Chen, and James J. Dignam. "Biomarker-Driven Oncology Clinical Trials: Key Design Elements, Types, Features, and Practical Considerations." JCO Precision Oncology, no. 3 (December 2019): 1–12. http://dx.doi.org/10.1200/po.19.00086.

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In this precision oncology era, where molecular profiling at the individual patient level becomes increasingly accessible and affordable, more and more clinical trials are now driven by biomarkers, with an overarching objective to optimize and personalize disease management. As compared with the conventional clinical development paradigms, where the key is to evaluate treatment effects in histology-defined populations, the choices of biomarker-driven clinical trial designs and analysis plans require additional considerations that are heavily dependent on the nature of biomarkers (eg, prognosti

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Veiga, Jackson T., Marcosiris A. O. Pessoa, Fabrício Junqueira, Paulo E. Miyagi, and Diolino J. dos Santos Filho. "A Systematic Modelling Procedure to Design Agent-Oriented Control to Coalition of Capabilities—In the Context of I4.0 as Virtual Assets (AAS)." Computers 10, no. 12 (2021): 161. http://dx.doi.org/10.3390/computers10120161.

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Manufacturing systems need to meet Industry 4.0 (I4.0) guidelines to deal with uncertainty in scenarios of turbulent demand for products. The engineering concepts to define the service’s resources to manufacture the products will be more flexible, ensuring the possibility of re-planning in operation. These can follow the engineering paradigm based on capabilities. The virtualization of industry components and assets achieves the RAMI 4.0 guidelines and (I4.0C), which describes the Asset Administration Shell (AAS). However, AAS are passive components that provide information about I4.0 assets.

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Dushkin, R. V., V. A. Lelecova, and K. Yu Eidemiller. "System of Operations on Associative Heterarchical Memory." Programmnaya Ingeneria 14, no. 2 (2023): 69–76. http://dx.doi.org/10.17587/prin.14.69-76.

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Text processing in natural language remains an important task for the field of development of artificial intelligence methods and tools. Since the twentieth century, artificial intelligence methods have been divided into two paradigms — top-down and bottom-up. The methods of the ascending paradigm are difficult to interpret in the form of the output of natural language, and the methods of the descending paradigm are difficult to actualize information. Taking into account the authors approach to the construction of artificial intelligence agents, the processing of natural language must be perfo

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Ezell, Barry, Christopher Lynch, and Patrick Hester. "Methods for Weighting Decisions to Assist Modelers and Decision Analysts: A Review of Ratio Assignment and Approximate Techniques." Applied Sciences 11, no. 21 (2021): 10397. http://dx.doi.org/10.3390/app112110397.

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Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system.

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K.Shantha Shalini. "Decentralized Machine Learning for Dynamic Resource Optimization in Wireless Networks using Reinforcement Learning." Journal of Electrical Systems 20, no. 5s (2024): 2025–33. http://dx.doi.org/10.52783/jes.2539.

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Efficient allocation of resources is crucial for optimizing wireless networks that face constraints in bandwidth, power, and spectrum. This paper proposes a decentralized reinforcement learning (RL) model that departs from traditional centralized paradigms to revolutionize resource optimization. The proposed model empowers individual wireless devices with autonomous decision-making capabilities, enhancing adaptability and scalability by leveraging Deep Q-Network (DQN) and Proximal Policy Optimization (PPO). The innovative integration of memory mechanisms facilitates learning from past experien

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Ali, Malik Mohammed. "AI-Forge - Your Coding Assistant." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 3918–23. https://doi.org/10.22214/ijraset.2025.69166.

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The need for quicker development cycles, better teamwork, and shorter technical onboarding times has increased in the modern era of software innovation, especially in huge codebases and enterprise-grade software systems. When growing modular architectures, maintaining old systems, or integrating new developers, traditional development pipelines frequently run into problems. A recurring barrier to guaranteeing code understanding, consistency, and maintainability is the enormous complexity of these systems, which is exacerbated by poor documentation and the dispersed structure of development tea

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Gong, Tao, Jia Jia Zhou, and Lei Qi. "Intelligent Techniques in Teaching Science of Artificial Immune System." Applied Mechanics and Materials 48-49 (February 2011): 637–40. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.637.

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Building on three theoretical paradigms (student model, ICAI model, and multi-dimension education immune agent), some intelligent techniques are proposed and designed to teach Fuzzy Mathematics and Science of Artificial Immune System in a web-based way. The goal of the teaching methodology is a new learning, which is interactive, sharing, open, cooperative, and autonomous. The great difference between traditional approaches for teaching such knowledge and the new approach in this paper is the centre of teaching. The traditional teaching is centered with teachers but the new teaching is centere

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Dushkin, R. V., V. A. Lelekova, V. Y. Stepankov, and S. Fadeeva. "Structure of associative heterarchical memory." Russian Technological Journal 10, no. 5 (2022): 7–15. http://dx.doi.org/10.32362/2500-316x-2022-10-5-7-15.

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Objectives. Since the 20th century, artificial intelligence methods can be divided into two paradigms: top-down and bottom-up. While the methods of the ascending paradigm are difficult to interpret as natural language outputs, those applied according to the descending paradigm make it difficult to actualize information. Thus, natural language processing (NLP) by artificial intelligence remains a pressing problem of our time. The main task of NLP is to create applications that can process and understand natural languages. According to the presented approach to the construction of artificial int

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Vishwajeet, Dilip Kadam. "Agents In Mainstream Economic Theory: An Analytical Inquiry." Young Researcher 14, no. 1C (2025): 209–16. https://doi.org/10.5281/zenodo.14936476.

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<em>Various paradigms in mainstream economic theory (MET) appear to have conceptualized an internalist, individualist and abstract notion of the agency/subjectivity/individuality. If MET makes the individual central to its analysis, criterion of identity and individuation must be applied to examine whether MET constructs an adequate and a substantive notion of the individual. Following Cartesian-Newtonian dualism of subjective inwardness-objective world and Smithian notion of a self-interested individual, cardinal utility approach of neo-classical economics constructs the individual as a utili

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Lehmann, Joel, Andreas Lober, Tim Häußermann, et al. "The Anatomy of the Internet of Digital Twins: A Symbiosis of Agent and Digital Twin Paradigms Enhancing Resilience (Not Only) in Manufacturing Environments." Machines 11, no. 5 (2023): 504. http://dx.doi.org/10.3390/machines11050504.

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Due to the growing environmental and geopolitical challenges nowadays, which are causing supply chain complications, industry and society are facing significant new objections. As a complement and extension to the technology-driven premises of Industry 4.0, the value-driven Industry 5.0 focuses on society and the environment. Human centricity, sustainability, and resilience should become a more integral part of both industrial and societal revolutions. One of the enabler technologies for both is the Digital Twin (DT). In order to make DTs intelligent, they must become active, online, goal-seek

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Isnandar, Suroso, Jonathan F. Simorangkir, Kevin M. Banjar-Nahor, Hendry Timotiyas Paradongan, and Nanang Hariyanto. "A Multiparadigm Approach for Generation Dispatch Optimization in a Regulated Electricity Market towards Clean Energy Transition." Energies 17, no. 15 (2024): 3807. http://dx.doi.org/10.3390/en17153807.

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In Indonesia, the power generation sector is the primary source of carbon emissions, largely due to the heavy reliance on coal-fired power plants, which account for 60% of electricity production. Reducing these emissions is essential to achieve national clean energy transition goals. However, achieving this initiative requires careful consideration, especially regarding the complex interactions among multiple stakeholders in the Indonesian electricity market. The electricity market in Indonesia is characterized by its non-competitive and heavily regulated structure. This market condition often

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Kazakov, Alexander, Anna Lempert, and Alexander Stolbov. "On technology for modeling and forecasting the interrelated development of regional fuel and energy complexes of Russia and Mongolia." E3S Web of Conferences 209 (2020): 07019. http://dx.doi.org/10.1051/e3sconf/202020907019.

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The paper considers the main ideas of proposed computational technology for scenario modeling and forecasting the development of the national fuel and energy complexes of Russia and Mongolia, regarding to the intercountry trade in fuel and energy resources. The proposing technology exploits the ideas of multi-agent systems (MASs) and agent-based simulation models (ABSMs) as they can act as unifying means for different types of decision-making methods by distributed objects. Methodological principles and architecture for ABSM of the national fuel and energy complexes of Russia and Mongolia were

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