Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving … optimization via temporal differences and Reinforcement Learning: Q-Learning, SARSA, and R-SMART algorithms, and policy search, via … API, Q-P-Learning, actor-critics, and learning automata · A special examination of neural-network-based function …

Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of … them image and speech recognition. Introduction to Deep Learning Using R provides a theoretical and practical understanding … of the models that perform these tasks by building upon the fundamentals of data science through machine learning and …

-- Reinforcement Learning for Dynamic Pricing and Automated Resource Allocation -- Combinatorial Auctions for Resource Allocation … -- Dynamic Pricing and Automated Resource Allocation Using Combinatorial Auctions -- Comparison of Reinforcement Learning and …-services. Recent methods of artificial intelligence, such as neural networks and reinforcement learning, and nature …

Learning -- Modeling and Algorithms -- Supervised Learning Models -- Supervised Learning Algorithms -- Support Vector Machine … -- Decision Tree Learning -- Part IV Understanding Scaling-Up Machine Learning -- Random Forest Learning -- Deep Learning Models …This book presents machine learning models and algorithms to address big data classification problems. Existing machine …

Die Ausführungen in diesem Buch zeigen auf, wie durch Konzeptionen der am kooperativen Lernprozess beteiligten aufbau …