The leading idea of epistemology in the Enlightenment tradition was foundation-theoretic: to reach knowledge, we must not legitimize our beliefs by external authorities, but instead justify them by rational arguments. Recently, the foundation-theoretic ideal of justification has come under attack, the chief criticism being that universal standards of justification are illusory because the problem of a regress of justification is unsolvable. Alternatives to foundation theory (coherentism, externalism, or dogmatism) have been developed that give up central claims of Enlightenment epistemology such as empirical support, cognitive accessibility, or rational justifiability. Optimality Justifications develops a new account of foundation-theoretic epistemology based on the method of optimality justifications. Optimality justifications offer a solution to the regress problem. Rather than striving for a priori demonstrations of reliability, which are impossible, they show that certain epistemic methods are optimal with regard to all accessible alternatives, which is more modestly but provably possible. In particular, optimality justifications can achieve a non-circular justification of deductive, inductive, and abductive reasoning. This volume pursues two goals: a general renewal of foundation-theoretic epistemology based on the account of optimality justifications, and the advancement of methods of optimality justification in important domains of epistemology and the philosophy of science, logic, and cognition. Connected with these goals is the aspiration to develop new ideas for mainstream epistemology, as well as for formal epistemology, philosophy of science, and cognitive science, which are intended to attract researchers, students, and all other readers interested in these fields.

A new approach to Hume's problem of induction that justifies the optimality of induction at the level of meta-induction. Hume's problem of justifying induction has been among epistemology's greatest challenges for centuries. In this book, Gerhard Schurz proposes a new approach to Hume's problem. Acknowledging the force of Hume's arguments against the possibility of a noncircular justification of the reliability of induction, Schurz demonstrates instead the possibility of a noncircular justification of the optimality of induction, or, more precisely, of meta-induction (the application of induction to competing prediction models). Drawing on discoveries in computational learning theory, Schurz demonstrates that a regret-based learning strategy, attractivity-weighted meta-induction, is predictively optimal in all possible worlds among all prediction methods accessible to the epistemic agent. Moreover, the a priori justification of meta-induction generates a noncircular a posteriori justification of object induction. Taken together, these two results provide a noncircular solution to Hume's problem. Schurz discusses the philosophical debate on the problem of induction, addressing all major attempts at a solution to Hume's problem and describing their shortcomings; presents a series of theorems, accompanied by a description of computer simulations illustrating the content of these theorems (with proofs presented in a mathematical appendix); and defends, refines, and applies core insights regarding the optimality of meta-induction, explaining applications in neighboring disciplines including forecasting sciences, cognitive science, social epistemology, and generalized evolution theory. Finally, Schurz generalizes the method of optimality-based justification to a new strategy of justification in epistemology, arguing that optimality justifications can avoid the problems of justificatory circularity and regress.

This book contains essays by A. John Simmons, perhaps the most innovative and creative of today's political philosophers.

This volume presents different conceptions of logic and mathematics and discuss their philosophical foundations and consequences. This concerns first of all topics of Wittgenstein's ideas on logic and mathematics; questions about the structural complexity of propositions; the more recent debate about Neo-Logicism and Neo-Fregeanism; the comparison and translatability of different logics; the foundations of mathematics: intuitionism, mathematical realism, and formalism. The contributing authors are Matthias Baaz, Francesco Berto, Jean-Yves Beziau, Elena Dragalina-Chernya, Günther Eder, Susan Edwards-McKie, Oliver Feldmann, Juliet Floyd, Norbert Gratzl, Richard Heinrich, Janusz Kaczmarek, Wolfgang Kienzler, Timm Lampert, Itala Maria Loffredo D'Ottaviano, Paolo Mancosu, Matthieu Marion, Felix Mühlhölzer, Charles Parsons, Edi Pavlovic, Christoph Pfisterer, Michael Potter, Richard Raatzsch, Esther Ramharter, Stefan Riegelnik, Gabriel Sandu, Georg Schiemer, Gerhard Schurz, Dana Scott, Stewart Shapiro, Karl Sigmund, William W. Tait, Mark van Atten, Maria van der Schaar, Vladimir Vasyukov, Jan von Plato, Jan Woleński and Richard Zach.

This sequel to volume 19 of Handbook on Statistics on Stochastic Processes: Modelling and Simulation is concerned mainly with the theme of reviewing and, in some cases, unifying with new ideas the different lines of research and developments in stochastic processes of applied flavour. This volume consists of 23 chapters addressing various topics in stochastic processes. These include, among others, those on manufacturing systems, random graphs, reliability, epidemic modelling, self-similar processes, empirical processes, time series models, extreme value therapy, applications of Markov chains, modelling with Monte Carlo techniques, and stochastic processes in subjects such as engineering, telecommunications, biology, astronomy and chemistry. particular with modelling, simulation techniques and numerical methods concerned with stochastic processes. The scope of the project involving this volume as well as volume 19 is already clarified in the preface of volume 19. The present volume completes the aim of the project and should serve as an aid to students, teachers, researchers and practitioners interested in applied stochastic processes.

This special issue documents the results of a workshop on and with Alvin Goldman at the University of Düsseldorf in May, 2008. The topic was Reliable Knowledge and Social Epistemology. The volume contains the written versions of all papers given at the workshop, divided into five chapters and followed by Alvin Goldman's replies in the sixth and final chapter. The contributions of the first chapter (E. Brendel, C. Jäger, and G. Schurz) address general questions of social epistemology, veritism and externalism, including critical reflections on Goldman's notion of 'weak knowledge'. The subsequent chapter (T. Grundmann and P. Baumann) examines problems which are involved in the search for an adequate explication of reliabilism. In the third chapter, E. Olsson, J. Horvath, C. Piller and M. Werning discuss Goldman and Olsson's account of the problem of the value of knowledge. In the fourth chapter (M. Baurmann & G. Brennan, and O. Scholz) two specific aspects of the social dimension of knowledge are investigated: the relation between knowledge and democracy as well as the definition and recognition of expertise. The fifth chapter (A. Newen & T. Schicht) discusses another part of Goldman's cognitive epistemology, namely his simulation theory of mindreading. Goldman gives detailed replies to all parts of the papers in the final chapter. He thereby clarifies the many aspects of his philosophy and proposes amendments of earlier positions of his.

Going beyond current books on privacy and security, this book proposes specific solutions to public policy issues pertaining to online privacy and security. Requiring no technical or legal expertise, it provides a practical framework to address ethical and legal issues. The authors explore the well-established connection between social norms, privacy, security, and technological structure. They also discuss how rapid technological developments have created novel situations that lack relevant norms and present ways to develop these norms for protecting informational privacy and ensuring sufficient information security.