Andere Kunden interessierten sich auch für
![A General View of Normalisation through Atomic Flows]( "A General View of Normalisation through Atomic Flows")
A General View of Normalisation through Atomic Flows38,99 €![Mathematics and Philosophy: Exploring the Deep Connections]( "Mathematics and Philosophy: Exploring the Deep Connections")
Mathematics and Philosophy: Exploring the Deep Connections29,99 €![Normalization of nonlinear representations of Lie algebras]( "Normalization of nonlinear representations of Lie algebras")
Normalization of nonlinear representations of Lie algebras22,99 €![Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics]( "Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics")
Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics153,99 €![Bayesian Inference for the Simple and Mixture of Laplace Distribution]( "Bayesian Inference for the Simple and Mixture of Laplace Distribution")
Bayesian Inference for the Simple and Mixture of Laplace Distribution51,99 €![Exact, efficient and computationally feasible inference]( "Exact, efficient and computationally feasible inference")
Exact, efficient and computationally feasible inference44,99 €![Statistical Inference for Heavy Tailed Time Series and Vectors]( "Statistical Inference for Heavy Tailed Time Series and Vectors")
Statistical Inference for Heavy Tailed Time Series and Vectors45,99 €
This book is presenting the calculus of structures, a recently developed proof-theoretic formalism using deep inference. According to this approach, inference rules can apply arbitrarily deep inside formulas. It follows that derivations are now symmetric instead of tree-shape objects. A formal system for classical predicate logic is presented and compared with the corresponding sequent calculus. They are both analytic systems but locality can only be obtained with deep inference, meaning that the effort of applying a rule is always bounded. Then we investigate what normal forms of deductions have been defined. Besides cut elimination, we can adopt two other notions of normalisation that allow cuts inside a derivation. The focus is on common things and differences between normalisation in deep and shallow inference.