A Novel Approach for Designing a Cognitive Sugarscape Cellular Society Using An Extended Moren Network. Issue 2 (2nd April 2016)

• Record Type: Journal Article
• Authors: Maleki, Masumeh; Nourafza, Nasim; Setayeshi, Saeed
• Is Part Of: Intelligent automation & soft computing. Volume 22:Issue 2(2016)
• Page Start: 193
• Page End: 201
• Publication Date: 2016-04-02
• Subjects: Artificial life -- artificial society -- Sugarscape model -- cognitive science -- Moren algorithm; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2015.1090720
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: ' Artificial life' is a term used to describe man-made systems that have been designed to behave in ways that simulate the behavior of natural living systems. Agent-based modeling of social processes is called 'artificial society.' The Sugarscape model is used to model, interpret, and organize social, political, and economic processes in an artificial society. In science, cognition refers to a whole series of mental processes, including attention, memory, language comprehension and production, and learning. The aim of this study was to develop a cognitive Sugarscape model. A Sugarscape model was designed, and the agents were placed in the environment randomly; the parameters of the model, such as sugar level and metabolism, were assigned to the agent randomly. In the present study, learning was applied in the Sugarscape model by the Moren algorithm and compared with the learner Sugarscape model that used the Boltzmann learning algorithm in previous studies. The results of the comparison showed that the number of agents in the sugar peaks in the convergent time of the cognitive Sugarscape model exceeded those in the learner Sugarscape model that used the Boltzmann learning algorithm.