Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Reinforcement Learning Rules in a Repeated Game
Computational Economics
Pseudo-convergent Q-Learning by Competitive Pricebots
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
A machine-learning approach to automated negotiation and prospects for electronic commerce
Journal of Management Information Systems - Special issue: Information technology and its organizational impact
Electronic marketplace definition and classification: literature review and clarifications
Enterprise Information Systems
Learning bidding strategies with autonomous agents in environments with unstable equilibrium
Decision Support Systems
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Business-to-business (B2B) exchanges are expected to bring about lower prices for buyers through reverse auctions. Analysis of such settings for seller pricing behavior often points to mixed-strategy equilibria. In real life, it is plausible that managers learn this complex ideal behavior over time. We modeled the two-seller game in a synthetic environment, where two agents use a reinforcement learning (RL) algorithm to change their pricing strategy over time. We find that the agents do indeed converge towards the theoretical Nash equilibrium. The results are promising enough to consider the use of artificial learning mechanisms in electronic marketplace transactions.