Discovering sensing capability in multi-agent systems

"What should be the sensing capabilities of agents in a Multi-Agent System be to solve a problem efficiently, quickly and economicly? This question often appears when trying to solve a problem using Multi-Agent Systems. This paper introduces a method to find these sensing capabilities in order...

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Autores principales: Parpaglione, María Cristina, Santos, Juan Miguel
Formato: Ponencias en Congresos
Lenguaje:Inglés
Publicado: 2022
Materias:
SISTEMAS MULTIAGENTES
ALGORITMOS GENETICOS
APRENDIZAJE POR REFUERZO
Acceso en línea:http://ri.itba.edu.ar/handle/123456789/3905
Aporte de:
Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA) de Instituto Tecnológico de Buenos Aires (ITBA)
id I32-R138-123456789-3905
record_format dspace
spelling I32-R138-123456789-39052022-12-07T14:13:59Z Discovering sensing capability in multi-agent systems Parpaglione, María Cristina Santos, Juan Miguel SISTEMAS MULTIAGENTES ALGORITMOS GENETICOS APRENDIZAJE POR REFUERZO "What should be the sensing capabilities of agents in a Multi-Agent System be to solve a problem efficiently, quickly and economicly? This question often appears when trying to solve a problem using Multi-Agent Systems. This paper introduces a method to find these sensing capabilities in order to solve a given problem. To achieve this, the sensing capability of an agent is modeled by a parametrized function and then Genetic Algorithms are used to find the parameters’ values. The individual behavior of the agents are found with Reinforcement Learning." 2022-06-02T19:20:44Z 2022-06-02T19:20:44Z 2010 Ponencias en Congresos 978-0-7695-4400-7 http://ri.itba.edu.ar/handle/123456789/3905 en application/pdf
institution Instituto Tecnológico de Buenos Aires (ITBA)
institution_str I-32
repository_str R-138
collection Repositorio Institucional Instituto Tecnológico de Buenos Aires (ITBA)
language Inglés
topic SISTEMAS MULTIAGENTES
ALGORITMOS GENETICOS
APRENDIZAJE POR REFUERZO
spellingShingle SISTEMAS MULTIAGENTES
ALGORITMOS GENETICOS
APRENDIZAJE POR REFUERZO
Parpaglione, María Cristina
Santos, Juan Miguel
Discovering sensing capability in multi-agent systems
topic_facet SISTEMAS MULTIAGENTES
ALGORITMOS GENETICOS
APRENDIZAJE POR REFUERZO
description "What should be the sensing capabilities of agents in a Multi-Agent System be to solve a problem efficiently, quickly and economicly? This question often appears when trying to solve a problem using Multi-Agent Systems. This paper introduces a method to find these sensing capabilities in order to solve a given problem. To achieve this, the sensing capability of an agent is modeled by a parametrized function and then Genetic Algorithms are used to find the parameters’ values. The individual behavior of the agents are found with Reinforcement Learning."
format Ponencias en Congresos
author Parpaglione, María Cristina
Santos, Juan Miguel
author_facet Parpaglione, María Cristina
Santos, Juan Miguel
author_sort Parpaglione, María Cristina
title Discovering sensing capability in multi-agent systems
title_short Discovering sensing capability in multi-agent systems
title_full Discovering sensing capability in multi-agent systems
title_fullStr Discovering sensing capability in multi-agent systems
title_full_unstemmed Discovering sensing capability in multi-agent systems
title_sort discovering sensing capability in multi-agent systems
publishDate 2022
url http://ri.itba.edu.ar/handle/123456789/3905
work_keys_str_mv AT parpaglionemariacristina discoveringsensingcapabilityinmultiagentsystems
AT santosjuanmiguel discoveringsensingcapabilityinmultiagentsystems
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