Trading Agents’ Negotiation in Business Management Using Demand Functions: Simulation Experiments with Binomial Distribution
Author(s) -
Roman Šperka,
Marek Spišák
Publication year - 2014
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2014.08.202
Subject(s) - computer science , negotiation , function (biology) , key (lock) , multi agent system , process (computing) , operations research , core (optical fiber) , artificial intelligence , computer security , telecommunications , evolutionary biology , political science , law , biology , engineering , operating system
The aim of this paper is to propose an experimental business management approach to cover a seller-to-customer price negotiation in an agent-based simulations. The core element in this approach is the price negotiation. We used Marshallian demand function and a Cobb-Douglas utility function in the negotiation process. Moreover, multi-agent model is proposed and implemented in Jade development platform. Its task is to serve as a simulation framework for the trading processes execution. The main background of this framework is to be integrated in management information systems as a decision support module for a prediction of key performance indicators of a virtual company. A binomial distribution was used in presented experiments to simulate the quantity of negotiated commodities. The paper firstly presents some of the existing principles about consumer behavior, agent-based modeling and simulation in the same area and demand function theory. Secondly, presents multi-agent model and demand functions negotiations more formally. Finally, shows some of the simulation results in a trading processes throughout one year of selling commodities to consumers. The results obtained show that the demand functions could be properly used to simulate trading processes
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