Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Self-Organizing Maps
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Neuro-Dynamic Programming
Dynamic Programming
Revenue Management in a Dynamic Network Environment
Transportation Science
A cost-based multi-unit resource auction for service-oriented grid computing
GRID '07 Proceedings of the 8th IEEE/ACM International Conference on Grid Computing
| Hi-index | 0.00 |
Pricing of information services gains an increasing importance in an IT environment, which is characterized by more and more decentralized computing resources (e.g. P-2-P computing). Even if pricing theory represents a kernel domain of economic research the pricing problem related to automated information production processes could not be handled satisfactory. This stems from the combination of high fixed costs with negligible variable costs. Especially in airline industries this problem is addressed by heuristics in the so called "Yield Management" (YM) domain. The paper presented here, shows the transferability of these methods to the information production and services domain. Pricing a bundle of complementary resources can not be solved by the simple addition of value functions. Therefore we introduce Machine Learning (ML) techniques to master complexity. Artificial Neural Networks (ANN) are used for the joint representation of the multidimensional value functions and Genetic Algorithms (GA) should help train them in a first effort. While this does not lead to outstanding results, we try Reinforcement Learning (RL) in a second approach. This ML method provides encouraging results for efficient adaptive pricing of resource attribution related to the multidimensional YM problem.