well-established self-learning algorithm) learns to profitably coordinate on either a fixed price or on asymmetric price …A novel debate within competition policy and regulation circles is whether autonomous machine learning algorithms may … learn to collude on prices. We show that when fims face short-run price commitments, independent Q-learning (a simple but …

data streams. Numerous machine learning-based models are developed to detect the concept drift in machine learning … devises dynamic streaming data analytics depending on the optimized hybrid deep learning classifier and Optimized Key … Windowing (OKW) approach to effectively handle the time and memory constraints. An optimized hybrid deep learning classifier is …

This paper discusses the question whether self-learning price-setting algorithms are able to coordinate their pricing …

algorithm. This solution efficiently determines the best machine learning model parameters from an infinite design space … biochar for heavy metals in soil, we proposed a novel approach based on machine learning models optimized by the Bayesian … learning models, with the random forest model exhibiting the best results (R2 = 0.998; RMSE = 0.027). Importance analysis of …