Making greed work in networks: a game-theoretic analysis of switch service disciplines
IEEE/ACM Transactions on Networking (TON)
Game theory, on-line prediction and boosting
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
Proceedings of the 1st ACM conference on Electronic commerce
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Gambling in a rigged casino: The adversarial multi-armed bandit problem
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Cooperation in multi-agent bidding
Decision Support Systems - Special issue: Formal modeling and electronic commerce
Autonomous Agents and Multi-Agent Systems
A Dialogue Game Protocol for Agent Purchase Negotiations
Autonomous Agents and Multi-Agent Systems
Multi-Attribute Dynamic Pricing for Online Markets Using Intelligent Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
A dynamic pricing approach in e-commerce based on multiple purchase attributes
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
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Past research has been concerned with the potential of embedding deterministic pricing algorithms into {\em pricebots}: software agents used by on-line sellers to automatically price Internet goods. In this work, probabilistic pricing algorithms based on {\em no-regret\/} learning are explored, in both high-information and low-information settings. It is shown via simulations that the long-run empirical frequencies of prices in a market of no-regret pricebots can converge to equilibria arbitrarily close to an asymmetric Nash equilibrium; however, instantaneous price distributions need not converge.