Machine Intelligence for Materials Science Artificial and Intelligent Matter

Preface.- 1. Introduction: Artificial Intelligence and Intelligent Matter.- Part I: Introduction to Artificial Intelligence.- 2. Introduction to Artificial Intelligence.- 3. An Introduction to Reinforcement Learning – In Artificial and Biological Control Systems.- 4. An Introduction to Reservoir Computing.- Part II: Applications of Artificial Intelligence to Nanosystems. 5. Learning Dynamical Systems from Data.- 6. Machine Learning Approaches to Classical Density Functional Theory.- 7. Machine Learning in Quantum Density Functional Theory.- 8. Generative Deep learning for the Inverse Design of Materials.- 9. Machine Learning for Identifying Dynamical Phases Intopologicallasers.- 10. Artificial Intelligence Reshaping the Semiconductor Metrology.- 11. Machine Learning for Active Matter.- Part III: Implementations of Artificial Intelligence in Nanosystems.- 12. A Primer on Neuromorphic Hardware: Underlying Principles and Approaches – From Sensors to Processors.- 13. Towards Intelligent Active Particles.- 14. Intelligent Matter Consisting of Active Particles.- 15. Neural Networks Consisting of DNA.- 16. Intelligence Without a Brain – Perspectives from the Aneural Slime Mold as a Computing Model for Artificial Intelligence.- 17. Integrated Photonics for Neuromorphic Computing.- 18. Time-multiplexed Reservoir Computing with Semiconductor Laser Systems.- 19. Neuromorphic Spintronics.- 20. Machine Learning with Quantum Computers.- Part IV: Philosophical Aspects.- 21. Normativity and the Intelligent Matter Framework.- 22. What Is It Like To Be a Nail? – The Intentions of Matter.- 23. Rethinking Computational Implementation Through Symphoria.- 24. Ethical Aspects of Artificial Intelligence in Nanoscience.