Author(s)

Xiang Xie ¹, Heting Jia ², Hanya Chen ³, Kai Pan ¹, Liming Huang ⁴, Shixu Li ⁵

Affiliation(s)

¹ China Petroleum Planning and Engineering Institute, Beijing, China
² School of Economics and Management, Dalian University of Technology, Dalian, China
³ School of Economics and Management, Beijing University of Chemical Technology, Beijing, China
⁴ China National Petroleum Corporation Hunan Sales Branch, Changsha, China
⁵ Dalian PetroChina Kunlun Gas Co., Ltd, Dalian, China

Corresponding Author

Heting Jia

ABSTRACT

The simulation method based on multi-agent agents is a common approach for analyzing market equilibrium in online trading markets. The accurate simulation of natural gas quotation decision-making by intelligent agents is crucial to ensuring the consistency of simulation results with market phenomena. To enable intelligent agents to effectively describe the real quotation strategies of natural gas suppliers across diverse and complex market environments, we developed a natural gas supplier intelligent agent quotation model incorporating limited rationality features through an analysis of bidding strategy characteristics and psychological mechanisms. This model encompasses capacity segmentation and quotation strategy space construction based on multiple psychological accounts, as well as a reinforcement learning model for domain search within the strategy space that reflects cautious adjustment and gradual trial-and-error psychology. Through this approach, our model successfully simulates the limited rationality in the quotation behavior of natural gas suppliers. Finally, we validated the effectiveness of our limited rationality intelligent agent model using an illustrative example and analyzed its impact on market equilibrium.

KEYWORDS

Natural Gas Suppliers, Online Transaction, Multi-agent-based Simulation, Limited Rational

CITE THIS PAPER

Xiang Xie, Heting Jia, Hanya Chen, Kai Pan, Liming Huang, Shixu Li, Multi-agent-based Simulation Model for the Limited Rational Pricing Behavior of Natural Gas Suppliers in Online Transaction Markets. Information Systems and Economics (2024) Vol. 5: 58-67. DOI: http://dx.doi.org/10.23977/infse.2024.050408.

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