Rolf Haenni – författare

This book constitutes the thoroughly refereed conference proceedings of the 5th International Conference on E-Voting and Identity, VoteID 2015, held in Bern, Switzerland, in September 2015. The 10 revised full papers presented, including one keynote and three invited talks, were carefully selected from 26 submissions. The papers deal with real-world electronic systems; advanced voting protocols; document analysis, machine-checked reasoning, e-voting system in court.

This book constitutes the thoroughly refereed conference proceedings of the 5th International Conference on E-Voting and Identity, VoteID 2015, held in Bern, Switzerland, in September 2015. The 10 revised full papers presented, including one keynote and three invited talks, were carefully selected from 26 submissions. The papers deal with real-world electronic systems; advanced voting protocols; document analysis, machine-checked reasoning, e-voting system in court.

While probabilistic logics in principle might be applied to solve a range of problems, in practice they are rarely applied - perhaps because they seem disparate, complicated, and computationally intractable. This programmatic book argues that several approaches to probabilistic logic fit into a simple unifying framework in which logically complex evidence is used to associate probability intervals or probabilities with sentences. Specifically, Part I shows that there is a natural way to present a question posed in probabilistic logic, and that various inferential procedures provide semantics for that question, while Part II shows that there is the potential to develop computationally feasible methods to mesh with this framework. The book is intended for researchers in philosophy, logic, computer science and statistics. A familiarity with mathematical concepts and notation is presumed, but no advanced knowledge of logic or probability theory is required.

While probabilistic logics in principle might be applied to solve a range of problems, in practice they are rarely applied - perhaps because they seem disparate, complicated, and computationally intractable. This programmatic book argues that several approaches to probabilistic logic fit into a simple unifying framework in which logically complex evidence is used to associate probability intervals or probabilities with sentences. Specifically, Part I shows that there is a natural way to present a question posed in probabilistic logic, and that various inferential procedures provide semantics for that question, while Part II shows that there is the potential to develop computationally feasible methods to mesh with this framework. The book is intended for researchers in philosophy, logic, computer science and statistics. A familiarity with mathematical concepts and notation is presumed, but no advanced knowledge of logic or probability theory is required.