Using modular neural networks to model self-consciousness and self-representation for artificial entities

Martínez Luaces, Milton; Gayoso Rocha, Celina; Pazos Sierra, Juan y Rodríguez-Patón Aradas, Alfonso (2008). Using modular neural networks to model self-consciousness and self-representation for artificial entities. "International journal of mathematics and computers in simulation", v. 2 (n. 2); pp. 163-170. ISSN 1998-0159.

Descripción

Título: Using modular neural networks to model self-consciousness and self-representation for artificial entities
Autor/es:
  • Martínez Luaces, Milton
  • Gayoso Rocha, Celina
  • Pazos Sierra, Juan
  • Rodríguez-Patón Aradas, Alfonso
Tipo de Documento: Artículo
Título de Revista/Publicación: International journal of mathematics and computers in simulation
Fecha: 2008
Volumen: 2
Materias:
Palabras Clave Informales: Holons, Modular neural networks, Self-conciousness, Self-representation, Holones, Redes neuronales modulares,Auto-conciencia, Auto-representación.
Escuela: Facultad de Informática (UPM) [antigua denominación]
Departamento: Inteligencia Artificial
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this paper, a cognitive architecture for self-consciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals'representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons’ cognitive architecture that enables dynamic self-representation. We analyse the effect of holon interaction, focusing on the evolution of the holon’s abstract self-representation. Finally, the results are explained and analysed and conclusions drawn.

Más información

ID de Registro: 15568
Identificador DC: http://oa.upm.es/15568/
Identificador OAI: oai:oa.upm.es:15568
URL Oficial: http://www.naun.org/multimedia/NAUN/mcs/
Depositado por: Memoria Investigacion
Depositado el: 03 Jun 2013 16:42
Ultima Modificación: 21 Abr 2016 15:43
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