Péter Érdi – författare

Human beings are competitive. We want to know who is the strongest, who is the richest, and who is the cleverest of all. Some situations, like ranking people based on height, can be ranked in objective ways. However, many "Top Ten" lists are based on subjective categorization and give only the illusion of objectivity. In fact, we don't always want to be seen objectively since we don't mind having a better image or rank than deserved. Ranking: The Unwritten Rules of the Social Game We All Play applies scientific theories to everyday experience by raising and answering questions like: Are college ranking lists objective? How do we rank and rate countries based on their fragility, level of corruption, or even happiness? How do we find the most relevant web pages? How are employees ranked? This book is for people who have a neighbor with a fancier car; employees, who are being ranked by their supervisors; managers, who are involved in ranking but may have qualms about the process; businesspeople interested in creating better visibility for their companies; scientists, writers, artists, and other competitors who would like to see themselves at the top of a success list; or college students who are just preparing to enter a new phase of social competition. Readers will engage in an intellectual adventure to better understand the difficulties of navigating between objectivity and subjectivity and to better identify and modify their place in real and virtual communities by combining human and computational intelligence.Translation editions available in German, Korean, Japanese, Complex Chinese, and Simplified Chinese.

This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.

This volume reviews the theory and simulation methods of stochastic kinetics by integrating historical and recent perspectives, presents applications, mostly in the context of systems biology and also in combustion theory. In recent years, due to the development in experimental techniques, such as optical imaging, single cell analysis, and fluorescence spectroscopy, biochemical kinetic data inside single living cells have increasingly been available. The emergence of systems biology brought renaissance in the application of stochastic kinetic methods.

As we all face the "replace or repair" dichotomy, readers will understand how to repair themselves, their relationships, and communities, accept the "new normal," and contribute to repairing the world.

The book offers an exciting, non-technical intellectual journey around applying feedback control to emerging and managing local and global crises, thus keeping the world on a sustainable trajectory. There is a narrow border between destruction and prosperity: to ensure reasonable growth but avoid existential risk, we must find the fine-tuned balance between positive and negative feedback.  This book addresses readers belonging to various generations, such as: young people growing up in a world where everything seems to be falling apart; people in their 30s and 40s who are thinking about how to live a fulfilling life;  readers in their 50s and 60s thinking back on life; and Baby Boomers reflecting on their past successes and failures.Albert-László Barabási, Robert Gray Dodge Professor of Network Science, Northeastern University: “In a world where interconnectedness has fostered global prosperity, it has also introduced vulnerabilities that can escalate local failures into worldwide crises. “Feedback” by Peter Erdi explores this double-edged sword, offering a solution through the power of feedback mechanisms. These tools are designed to mitigate the negative impacts of connectedness, steering the complexity of modern life towards outcomes that enhance human welfare.”Patrick Grim, Philosopher in Residence Visiting Scholar Center for Complex Systems University of Michigan: “Érdi demonstrates that many of the critical problems we face—from climate crises to economic instability to the threat of terrorism—operate as runaway feedback loops. The first challenge is to understand them.  The second is to introduce control mechanisms on the model of biological homeostasis—a different form of feedback—that will guide us toward a more sustainable social future.  Érdi applies the analytic tools of complex systems to some of the most complex issues we face.”Ichiro Tsuda, Specially Appointed Professor at Sapporo City University, Sapporo, Japan, leaving Chubu University Academy of Emerging Sciences (Director and Professor), Chubu University, Japan: “This book is dangerous, because of making your own consideration on feedback impossible to stop by a continual feedback process of yourself. Nevertheless, you must be given a method of finding very narrow boundaries between prosperity and destruction, therefore this book is extremely valuable. We all must read.”

This book presents the latest research in computational methods for modeling and simulating brain disorders. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.

This book presents the latest research in computational methods for modeling and simulating brain disorders. Mainly written for computational scientists eager to discover new application fields for their model, this book also benefits neurologists and psychiatrists wanting to learn about new methods.

This volume contains invited and contributed papers presented at the eighth edition of the International Summer School on Neural Networks, dedicated to Prof.EduardoR.Caianiello.Theschoolwasestablishedin1996byProf.Antonio Zichichi, director of the Ettore Maiorana Centre for Scienti?c Culture in Erice (Sicily), and Prof. Maria Marinaro, director of the International Institute for Advanced Scienti?c Studies in Vietri sul Mare, in Italy. The school is held each year,alternatingbetweenEriceandVietri,proposingsurveysonseveralresearch ?elds related to cybernetics studies and human-machine interaction. The eighth edition of the school was on cortical dynamics and was held in Erice. The contributions collected in this book are aimed at providing primarily high-level tutorial coverage of the ?elds related to cortical dynamics, repo- ing recent experimental and theoretical results investigating the processing, the transmission, and the imprinting of information in the brain, and important functions of the cortical area such as cortical rhythms, cortical neural plasticity, and their structural basis and functional signi?cance. Height surveys, reporting the most recent original results, are o?ered by specialists in the ?eld. Consequently, the volume may be used as a reference book on models of cortical dynamics from neuroscienceand physics. To this aim the volume is divided into two sections: fundamentals of cortical dynamics, and mathematical models of cortical dynamics.

This book is, of course about complexity. The title of the book, as you may recognize was motivated (excuse me for using this very mild expression) by Daniel Dennett’s Consciousness Explained [130]. Dennett’s intention was to explain consciousness as the emergent product of the interaction among c- stituents having physical and neural character. The goal of this book is to explain how various types of complexity emerge due to the interaction among constituents. There are many questions to be answered, how to understand, control, decompose, manage, predict the many-faced complexity. After tea- ing thissubjectforseveralyearsIfeelthatthe time hascome toputthe whole story together. The term “complex system” is a buzzword, but we certainly don’t have a single de?nition for it. There are several predominant features of compl- ity. Complex processes may show unpredictable behavior (which we still try to predict somehow), may lead to uncontrolled explosion (such in case of epilepsy, earthquake eruptions or stock market crashes). One of the char- teristic feature of simple systems is, that there is a single cause which implies a single e?ect. For large class of complex systems it is true that e?ects are fed back to modify causes. Biological cells belong to this class. Furthermore they are open to material, energetic and information ?ow by interaction with their environment, still they are organizationallyclosed units. Another aspect of complexity is the question how collective phenomena emerge by some se- organized mechanisms.

This book is, of course about complexity. The title of the book, as you may recognize was motivated (excuse me for using this very mild expression) by Daniel Dennett’s Consciousness Explained [130]. Dennett’s intention was to explain consciousness as the emergent product of the interaction among c- stituents having physical and neural character. The goal of this book is to explain how various types of complexity emerge due to the interaction among constituents. There are many questions to be answered, how to understand, control, decompose, manage, predict the many-faced complexity. After tea- ing thissubjectforseveralyearsIfeelthatthe time hascome toputthe whole story together. The term “complex system” is a buzzword, but we certainly don’t have a single de?nition for it. There are several predominant features of compl- ity. Complex processes may show unpredictable behavior (which we still try to predict somehow), may lead to uncontrolled explosion (such in case of epilepsy, earthquake eruptions or stock market crashes). One of the char- teristic feature of simple systems is, that there is a single cause which implies a single e?ect. For large class of complex systems it is true that e?ects are fed back to modify causes. Biological cells belong to this class. Furthermore they are open to material, energetic and information ?ow by interaction with their environment, still they are organizationallyclosed units. Another aspect of complexity is the question how collective phenomena emerge by some se- organized mechanisms.

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.

The two-volume set LNCS 7552 + 7553 constitutes the proceedings of the 22nd International Conference on Artificial Neural Networks, ICANN 2012, held in Lausanne, Switzerland, in September 2012. The 162 papers included in the proceedings were carefully reviewed and selected from 247 submissions. They are organized in topical sections named: theoretical neural computation; information and optimization; from neurons to neuromorphism; spiking dynamics; from single neurons to networks; complex firing patterns; movement and motion; from sensation to perception; object and face recognition; reinforcement learning; bayesian and echo state networks; recurrent neural networks and reservoir computing; coding architectures; interacting with the brain; swarm intelligence and decision-making; mulitlayer perceptrons and kernel networks; training and learning; inference and recognition; support vector machines; self-organizing maps and clustering; clustering, mining and exploratory analysis; bioinformatics; and time weries and forecasting.