Geodesic
Multiagent simulation of regional distributed
News of the Kabardin-Balkar scientific center of RAS, no. 1 (2011), pp. 101-107 Cet article a éte moissonné depuis la source Math-Net.Ru

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Multiagent simulation nowadays is considered as a very perspective methodology of studying regional and local markets. We use different types of agents, and consider time- and information-based factors, that affect agents’ behavior, especially information incompleteness and information asymmetry. The model is based on planning adaptive agents using dynamic decision networks as a formal basis of the agent’s decision-making. Agents maximize their expected utility (as a criterion function) with constraints defined by the properties of the agent and the environment.
Keywords: information asymmetry; information incompleteness; multi-agent simulation; mechanism design; decision making; bounded rationality. 
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A. O. Gurtuev; Z. Z. Ivanov; Z. V. Nagoev. Multiagent simulation of regional distributed. News of the Kabardin-Balkar scientific center of RAS, no. 1 (2011), pp. 101-107. http://geodesic.mathdoc.fr/item/IZKAB_2011_1_a17/

[1] V. L. Makarov, “Iskusstvennye obschestva”, Iskusstvennye obschestva, 1:1 (2006) | MR

[2] S. Rassel, P. Norvig, Iskusstvennyi intellekt: sovremennyi podkhod, 2-e izd.: per. s angl., Izdatelskii dom «Vilyams», Moskva, Sankt-Peterburg, Kiev, 2006

[3] E. Constantinides, “Influencing the online consumer's behaviour: the Web Experience”, Internet Research-Electronic Networking Applications and Policy, 2002, no. 14(2)

[4] R. Garcia-Flores, X. Z. Wang, G. E. Goltz, “Agent-based Information Flow for Process Industries' Supply Chain Modelling”, Computers and Chemical Engineering, 24 (2000) (2-7) | DOI

[5] S. H. Ha, S. M. Bae, S. C. Park, “Customer's Time-Variant Purchase Behaviour and Cor responding Marketing Strategies: An Online Retailer's Case”, Computers and Industrial Engineering, 2002, no. 43(4)

[6] N. Julka, R. Srinivasen, I. Karimi, “Agent-based supply chain Management-1: Frame work”, Computers and Chemical Engineering, 2002, no. 26(12) | Zbl

[7] D. O'Sullivan, D. Haklay, “Agent-based Models and Individualism: Is the World Agent-Based?”, Environment and Planning A, 2000, no. 32(8)

[8] E. Pettersen, A. B. Philpott, S. W. Wallace, “An Electricity Market Game Between Consumers, Retailers and Network Operators”, Decision Support Systems, 40 (2005) (3-4) | DOI

[9] R. Signorille, “Simulation of a Multi-Agent System for Retail Inventory Control: A Case Study”, Simulation-Transactions of the Society for Modelling and Simulation International, 78 (2002)