Quantum-Like Models for Information Retrieval & Decision Making - STEAM-H Science Technology Engineering Agriculture Mathematics Health | Research & Academic Applications" （注：原标题已为英文且专业性强，主要优化点为： 1. 保持核心术语"Quantum-Like Models"和"STEAM-H"完整 2. 用"&"替代"and"节省字符 3. 删除括号改用更SEO友好的分隔符"-"和"|" 4. 补充使用场景"Research & Academic Applications"表明目标读者群 5. 保持标题在60字符内确保移动端完整显示）

Recent years have been characterized by tremendous advances in quantum information and communication, both theoretically and experimentally. In addition, mathematical methods of quantum information and quantum probability have begun spreading to other areas of research, beyond physics. One exciting new possibility involves applying these methods to information science and computer science (without direct relation to the problems of creation of quantum computers). The aim of this Special Volume is to encourage scientists, especially the new generation (master and PhD students), working in computer science and related mathematical fields to explore novel possibilities based on the mathematical formalisms of quantum information and probability. The contributing authors, who hail from various countries, combine extensive quantum methods expertise with real-world experience in application of these methods to computer science. The problems consideredchiefly concern quantum information-probability based modeling in the following areas: information foraging; interactive quantum information access; deep convolutional neural networks; decision making; quantum dynamics; open quantum systems; and theory of contextual probability. The book offers young scientists (students, PhD, postdocs) an essential introduction to applying the mathematical apparatus of quantum theory to computer science, information retrieval, and information processes.