A General Cognitive Architecture for Agent-Based Modeling in Artificial Societies

Authored by Peijun Ye, Shuai Wang, Fei-Yue Wang

Date Published: 2018

DOI: 10.1109/tcss.2017.2777602

Sponsors: Chinese National Natural Science Foundation

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts

Model Code URLs: Model code not found

Abstract

Artificial Society is an analytical foundation of various complex eco- and social systems. Such system is usually implemented via multiagent approach. However, there is no consensus on how to model the agent's decision-making process, since different application scenarios concentrate on different facets. This, to some extent, hinders model reuse and system integration. This paper proposes a general cognitive architecture that attempts to adapt all the aspects of agent's decision-making in artificial societies, so that different programs and software can be reorganized and integrated conveniently. To illustrate its implementation, two simulations-emergent evacuation and population evolution-are conducted. These tests clearly show that the proposed architecture is able to support different agent-based models. Problems that might be encountered, as well as possible strategies, are also proposed in the end.

Tags

Agent-based modeling systems Artificial society Cognitive architecture (ca)