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

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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.
Funding Information
  • National Natural Science Foundation of China (61603381, 61533019, 71232006)
  • China Scholarship Council (201704910284)

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