Ponencia en Congreso:
Discovering sensing capability in multi-agent systems

dc.contributor.authorParpaglione, María Cristina
dc.contributor.authorSantos, Juan Miguel
dc.date.accessioned2022-06-02T19:20:44Z
dc.date.available2022-06-02T19:20:44Z
dc.date.issued2010
dc.description.abstract"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."en
dc.identifier.isbn978-0-7695-4400-7
dc.identifier.urihttp://ri.itba.edu.ar/handle/123456789/3905
dc.language.isoenen
dc.subjectSISTEMAS MULTIAGENTESes
dc.subjectALGORITMOS GENETICOSes
dc.subjectAPRENDIZAJE POR REFUERZOes
dc.titleDiscovering sensing capability in multi-agent systemsen
dc.typePonencias en Congresoses
dspace.entity.typePonencia en Congreso
itba.description.filiationFil: Parpaglione, María Cristina. Instituto Tecnológico de Buenos Aires; Argentina.
itba.description.filiationFil: Santos, Juan Miguel. Instituto Tecnológico de Buenos Aires; Argentina.

Archivos

Bloque original
Mostrando 1 - 1 de 1
Cargando...
Miniatura
Nombre:
Parpaglione_Santos_2010_ING_INFORMATICA_ponencia.pdf
Tamaño:
184.04 KB
Formato:
Adobe Portable Document Format
Descripción:
Ponencia_Parpaglione
Bloque de licencias
Mostrando 1 - 1 de 1
No hay miniatura disponible
Nombre:
license.txt
Tamaño:
1.6 KB
Formato:
Item-specific license agreed upon to submission
Descripción: