Predicting Human Decision-Making

丛 书 名：Synthesis Lectures on Artificial Intelligence and Machine Learning

版本说明：1

作     者：Ariel Rosenfeld Sarit Kraus 

I S B N：(纸本) 9783031000232 

出 版 社：Springer Cham 

出 版 年：1000年

页      数：XVI, 134页

主 题 词：Artificial Intelligence Machine Learning Mathematical Models of Cognitive Processes and Neural Networks 

摘      要：Human decision-making often transcends our formal models of rationality. Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as;. The book presents both the traditional and classical methods as well asthe most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.