Multi-agent systems (MAS) in the area of IoT and using a model with Distributed Shared Memory system (DSM)

Stefanova-Stoyanova, Varbinka; Stankov, Ivan

doi:10.1109/et50336.2020.9238153

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…Los MARS se definen como el conjunto de diferentes agentes inteligentes que tienen cierto nivel de autonomía que cooperan entre sí para alcanzar un objetivo común (Stefanova-Stoyanova & Stankov, 2020). Sin embargo el problema del DRL en los MARS dentro de la PCP es la presencia de diferentes agentes inteligentes que deben cumplir varias restricciones en un entorno cambiante para cumplir un objetivo común (Sagar et al, 2018).…”

Section: Planteamiento Del Problemaunclassified

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Aplicación de algoritmos de aprendizaje automático a sistemas robóticos multiagente para la programación y control de operaciones productivas y logísticas: una revisión de la literatura reciente

Velastegui,

Poler,

Díaz-Madroñero

2023

DyO

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Este artículo presenta una revisión bibliográfica de los algoritmos de aprendizaje automático utilizados para dar solución a la problemática de los MARS para la PCP productivas y logísticas. Se ha analizado y clasificado la información en base al criterio aplicación en las industrias donde los resultados más relevantes fueron con un 60% experimental, 13% celdas de producción, 7% simulación, 7% teórico y otro 13% que no se especifica. Se ha encontrado, además, varios algoritmos de aprendizaje IA, DL, DRL, QL, que se pueden aplicar en las industrias. El objetivo es construir un documento que sirva de punto de partida para investigadores y profesionales en el ámbito de algoritmos de aprendizaje automático en sectores industriales.

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Section: Planteamiento Del Problemaunclassified

“…Stefanova-Stoyanova & Stankov (2020) en su estudio manifiesta que la tecnología DSM con la revolución de MAS para loT, propone la creación de soluciones distribuidas finitas, al introducir funcionalidades complejas Tabla 5 Soluciones de la literatura de los MARS…”

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Aplicación de algoritmos de aprendizaje automático a sistemas robóticos multiagente para la programación y control de operaciones productivas y logísticas: una revisión de la literatura reciente

Velastegui,

Poler,

Díaz-Madroñero

2023

DyO

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“…These systems are composed of many homogeneous or heterogeneous intelligent software or hardware agents. They are agents with certain perception, communication, computing, and execution capabilities to form a system [20][21][22]. In other words, the swarm robot system can be a multi-agent system by properly designing the path tracking controller and the path profiles (i.e., several formation types).…”

Section: Introductionmentioning

confidence: 99%

Grey Estimator-Based Tracking Controller Applied to Swarm Robot Formation

Chen

Chiu

Lee³

2021

Axioms

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Mobile robots are widely used in many applications, while various types of mobile robots and their control researches have been proposed in literature. Since swarm robots have higher flexibility and capacity for teamwork, this paper presents a grey estimator-based tracking controller for formation trajectory tracking of swarm robots. First, wheel-type mobile robots are used and modeled for the controller design. Then, a grey dynamic estimator is developed to estimate the environmental disturbance and model uncertainty for linear feedback compensation. As a result, the asymptotic trajectory tracking is assured, so that the application on the swarm robot formation is achieved for a multi-agent system. The computational complexity is slightly reduced by the design. Finally, in order to verify the reliability of swarm robot formation, several types of formation are maintained by the grey estimator-based feedback linearization controller.

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“…The use of simulation tools is a common practice in developing MAS to anticipate the learning level and the cognitive agents' action performance [4][5][6][7]. For example, tools are used in the robot soccer domain to support simulation and setplays definition [8][9][10].…”

mentioning

confidence: 99%

Towards Automatic Code Generation for Robotic Soccer Behavior Simulation

Sales,

Fontes Magalhães Mascarenhas,

Simões

et al. 2024

J Intell Robot Syst

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Multi-Agent Systems (MAS) are an Artificial Intelligence (AI) branch where agents handle distributed nature tasks in a cooperative system. MAS is widely used in robotic systems in scenarios where multiple robots must cooperate. In this direction, the robot soccer domain has been used as a test bed to stimulate research in this area, as it reproduces some important features of these systems, such as coordination. Each soccer team member is an agent whose behavior must be coordinated with the other team members cooperating to win the game. Simulation tools are frequently used in this context to create rehearsed plays, called setplays, during team training. However, these tools generally have a limited set of behaviors, e.g., kicking, available to use in setplays, and new behaviors must be manually implemented. This implementation requires knowledge of specific source codes and a significant programming effort, in addition to leaving the behavior coupled and dependent on the tool. This work proposes the Robot Soccer Behavior Generator (RoboSocBG), a solution to develop new behaviors in the context of simulated soccer robots. It uses Model-Driven Development (MDD), an approach that enables the specification of behavior platform-independent models and code generation in specific tools. The solution was tested in our laboratory and validated in a case study. The results evidenced its feasibility to generate code in different platforms.

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Multi-agent systems (MAS) in the area of IoT and using a model with Distributed Shared Memory system (DSM)

Cited by 7 publications

References 15 publications

Aplicación de algoritmos de aprendizaje automático a sistemas robóticos multiagente para la programación y control de operaciones productivas y logísticas: una revisión de la literatura reciente

Aplicación de algoritmos de aprendizaje automático a sistemas robóticos multiagente para la programación y control de operaciones productivas y logísticas: una revisión de la literatura reciente

Grey Estimator-Based Tracking Controller Applied to Swarm Robot Formation

Towards Automatic Code Generation for Robotic Soccer Behavior Simulation

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