Introduction to Stochastic Dynamic Programming: Probability and Mathematical
Introduction to Stochastic Dynamic Programming: Probability and Mathematical
Discrete Prediction Games with Arbitrary Feedback and Loss
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Gambling in a rigged casino: The adversarial multi-armed bandit problem
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Producer-Supplier Contracts with Incomplete Information
Management Science
Multicriteria Optimization
Prediction, Learning, and Games
Prediction, Learning, and Games
Information Distortion in a Supply Chain: The Bullwhip Effect
Management Science
Competition for subscribers between mobile operators sharing a limited resource
GameNets'09 Proceedings of the First ICST international conference on Game Theory for Networks
Operations Research
Stability of alliances between service providers
ETM'10 Proceedings of the Third international conference on Incentives, overlays, and economic traffic control
| Hi-index | 0.00 |
In this article, we deal with the resolution of a dynamic game of interconnection between mobile network operators (MNOs) sharing their scarce resources and mobile virtual network operators (MVNOs) lacking the infrastructure but trying to bargain to send as much traffic as possible on the MNOs' networks. Besides consumers' perception of the MVNO's brand is based on a word-of-mouth process; the consumers' cheating probability being an exogeneous parameter. The difficulty arises from the fact that the MVNOs ignore the unused bandwidth volumes on both MNOs' networks and how these latter allocate it between the competitive MVNOs. In fact, to increase their revenues, the MVNOs need to learn as fast as possible the hidden information. Five learning strategies have been tested: (i) tit for tat, (ii) fictitious play, (iii) external regret minimization, (iv) repeated exploration-exploitation, (v) internal regret minimization. We check numerically that in general, solely the internal regret minimization strategy reaches a correlated equilibrium. Besides MVNOs' power relation and consumers' cheating probability play a central role in the learning rate and the resulting organization. Indeed either one of the MVNOs learns faster, capturing a larger part of the market while the other has no choice but to follow (leader/follower), or an implicit cooperation occurs i.e., both MVNOs learn and increase their performances simultaneously (peers).