Sequential decision making in artificial musical intelligence

Over the past 60 years, artificial intelligence has grown from a largely academic field of research to a ubiquitous array of tools and approaches used in everyday technology. Despite its many recent successes and growing prevalence, certain meaningful facets of computational intelligence have not been as thoroughly explored. Such additional facets cover a wide array of complex mental tasks which humans carry out easily, yet are difficult for computers to mimic. A prime example of a domain in which human intelligence thrives, but machine understanding is still fairly limited, is music. Over the last decade, many researchers have applied computational tools to carry out tasks such as genre identification, music summarization, music database querying, and melodic segmentation. While these are all useful algorithmic solutions, we are still a long way from constructing complete music agents, able to mimic (at least partially) the complexity with which humans approach music. One key aspect which hasn't been sufficiently studied is that of sequential decision making in musical intelligence. This thesis strives to answer the following question: Can a sequential decision making perspective guide us in the creation of better music agents, and social agents in general? And if so, how? More specifically, this thesis focuses on two aspects of musical intelligence: music recommendation and human-agent (and more generally agent-agent) interaction in the context of music. The key contributions of this thesis are the design of better music playlist recommendation algorithms; the design of algorithms for tracking user preferences over time; new approaches for modeling people's behavior in situations that involve music; and the design of agents capable of meaningful interaction with humans and other agents in a setting where music plays a roll (either directly or indirectly). Though motivated primarily by music-related tasks, and focusing largely on people's musical preferences, this thesis also establishes that insights from music-specific case studies can also be applicable in other concrete social domains, such as different types of content recommendation. Showing the generality of insights from musical data in other contexts serves as evidence for the utility of music domains as testbeds for the development of general artificial intelligence techniques. Ultimately, this thesis demonstrates the overall usefulness of taking a sequential decision making approach in settings previously unexplored from this perspectiveComputer Science

E-learning and Digital Training in Healthcare Education

This book is dedicated to the current trends and new challenges that have emerged from the new e-learning environment, focusing on its potential to revolutionize Healthcare Education and exploring how it may help to better prepare future healthcare professionals for their daily practice. “E-learning and Digital Training in Healthcare Education: Current Trends and New Challenges” contains several research articles focused on new insights into the use of interactive and intuitive e-learning tools and innovative teaching methodologies that engage healthcare students in the new web-based environment training. It also includes several case studies of ‘pathfinder’ e-learning initiatives and surveys related to the penetration and acceptance of digital training in Healthcare Education

Multi-Robot Systems: Challenges, Trends and Applications

This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics

Concepts and Approaches for Mars Exploration

Abstracts describe missions, mission elements or experiments for consideration in the 2005-2020 time frame. Also the technologies and the support necessary to achieve the results are discussed.NASA Headquarters; Lunar and Planetary Institutehosted by Lunar and Planetary Institute ; sponsored by NASA Headquarters, Lunar and Planetary Institute ; convener Scott Hubbard

Augmented Reality

There is at present no publication specifically dedicated to analyzing the philosophical implications of augmented reality. Applications cover diverse fields like psychopathology and education, implications concern issues as diverse as negative knowledge, group cognition, the internet of things, and ontological issues, among others. In this way, it is intended not only to generate answers, but also, to draw attention to new problems that arise with the diffusion of augmented reality. In order to contemplate these problems from diverse perspectives, the authors are from a variety of fields - philosophy, computer sciences, education, psychology, and many more. Accordingly, the volume offers varied and interesting contributions which are of interest to professionals from multiple disciplines