Understanding the feasibility of machine learning algorithms in a game theoretic environment for dynamic spectrum access.
Alisha ThapaliyaShamik SenguptaPublished in: SPECTS (2017)
Keyphrases
- machine learning algorithms
- game theoretic
- benchmark data sets
- game theory
- learning algorithm
- machine learning
- dynamic environments
- decision trees
- machine learning methods
- predictive accuracy
- decision problems
- learning problems
- machine learning approaches
- random forests
- rational agents
- nash equilibrium
- machine learning models
- coalitional games
- data sets
- trust model
- input features
- imperfect information
- regret minimization
- learning models
- nash equilibria
- agent behavior
- learning tasks
- agent programming
- minority game
- standard machine learning algorithms