期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2018
卷号：8
期号：1
页码：326-332
DOI：10.11591/ijece.v8i1.pp326-332
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Modeling higher order cognitive processes like human decision making come in three representational approaches namely symbolic, connectionist and symbolic-connectionist. Many connectionist neural network models are evolved over the decades for optimizing decision making behaviors and their agents are also in place. There had been attempts to implement symbolic structures within connectionist architectures with distributed representations. Our work was aimed at proposing an enhanced connectionist approach of optimizing the decisions within the framework of a symbolic cognitive model. The action selection module of this framework is forefront in evolving intelligent agents through a variety of soft computing models. As a continous effort, a Connectionist Cognitive Model (CCN) had been evolved by bringing a traditional symbolic cognitive process model proposed by LIDA as an inspiration to a feed forward neural network model for optimizing decion making behaviours in intelligent agents. Significanct progress was observed while comparing its performance with other varients.
其他摘要：Modeling higher order cognitive processes like human decision making come in three representational approaches namely symbolic, connectionist and symbolic-connectionist. Many connectionist neural network models are evolved over the decades for optimizing decision making behaviors and their agents are also in place. There had been attempts to implement symbolic structures within connectionist architectures with distributed representations. Our work was aimed at proposing an enhanced connectionist approach of optimizing the decisions within the framework of a symbolic cognitive model. The action selection module of this framework is forefront in evolving intelligent agents through a variety of soft computing models. As a continous effort, a Connectionist Cognitive Model (CCN) had been evolved by bringing a traditional symbolic cognitive process model proposed by LIDA as an inspiration to a feed forward neural network model for optimizing decion making behaviours in intelligent agents. Significanct progress was observed while comparing its performance with other varients.
