This book collects the extended abstracts of the accepted contributions to EuroComb21. A similar book is published at every edition of EuroComb (every two years since 2001) collecting the most recent advances in combinatorics, graph theory, and related areas. It has a wide audience in the areas, and the papers are used and referenced broadly.

This is an open access book. The book provides an overview of the state of research in developing countries – Africa, Latin America, and Asia (especially India) and why research and publications are important in these regions. It addresses budding but struggling academics in low and middle-income countries. It is written mainly by senior colleagues who have experienced and recognized the challenges with design, documentation, and publication of health research in the developing world. The book includes short chapters providing insight into planning research at the undergraduate or postgraduate level, issues related to research ethics, and conduct of clinical trials. It also serves as a guide towards establishing a research question and research methodology. It covers important concepts such as writing a paper, the submission process, dealing with rejection and revisions, and covers additional topics such as planning lectures and presentations. The book will be useful for graduates, postgraduates, teachers as well as physicians and practitioners all over the developing world who are interested in academic medicine and wish to do medical research.

The book presents research works developed within the Anthropological Theory of the Didactic (ATD) by senior and young researchers that participated in the Intensive Research Program “Advances in the anthropological theory of the didactic and their consequences in curricula and teacher education” held at the Centre de Recerca Matematica (CRM) in Barcelona. It is organized in three axes of current research on the ATD: teacher education and the professionalization of teaching; the curriculum problem in the historical transition from the classical paradigm of visiting works to the emerging didactic paradigm of questioning the world; and research in didactics at the university level.

This collection of extended abstracts summarizes the latest research as presented at "Frontiers in Electronic Materials", a Nature conference on correlation effects and memristive phenomena, which took place in 2012. The contributions from leading authors from the US, Japan, Korea, and Europe discuss breakthroughs and challenges in fundamental research as well as the potential for future applications. Hot topics covered include: Electron correlation and unusual quantum effects Oxide heterostructures and interfaces Multiferrroics, spintronics, ferroelectrics and flexoelectrics Processing in nanotechnology Advanced characterization techniques Superionic conductors, thermoelectrics, photovoltaics Chip architectures and computational concepts An essential resource for the researchers of today and tomorrow.

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.