Hardcover ISBN:  9780821835715 
Product Code:  CRMM/23 
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eBook ISBN:  9781470438678 
Product Code:  CRMM/23.E 
List Price:  $110.00 
MAA Member Price:  $99.00 
AMS Member Price:  $88.00 
Hardcover ISBN:  9780821835715 
eBook: ISBN:  9781470438678 
Product Code:  CRMM/23.B 
List Price:  $225.00 $170.00 
MAA Member Price:  $202.50 $153.00 
AMS Member Price:  $180.00 $136.00 
Hardcover ISBN:  9780821835715 
Product Code:  CRMM/23 
List Price:  $115.00 
MAA Member Price:  $103.50 
AMS Member Price:  $92.00 
eBook ISBN:  9781470438678 
Product Code:  CRMM/23.E 
List Price:  $110.00 
MAA Member Price:  $99.00 
AMS Member Price:  $88.00 
Hardcover ISBN:  9780821835715 
eBook ISBN:  9781470438678 
Product Code:  CRMM/23.B 
List Price:  $225.00 $170.00 
MAA Member Price:  $202.50 $153.00 
AMS Member Price:  $180.00 $136.00 

Book DetailsCRM Monograph SeriesVolume: 23; 2004; 215 ppMSC: Primary 68
The book consists of two sets of lecture notes devoted to slightly different methods of analysis of concurrent and probabilistic computational systems.
The first set of lectures develops a calculus of streams (a generalization of the set of natural numbers) based on the coinduction principle coming from the theory of coalgebras. It is now well understood that the interplay between algebra (for describing structure) and coalgebra (for describing dynamics) is crucial for understanding concurrent systems. There is a striking analogy between streams and formula calculus reminiscent of those appearing in quantum calculus. These lecture notes will appeal to anyone working in concurrency theory but also to algebraists and logicians.
The other set of lecture notes focuses on methods for automatically verifying probabilistic systems using techniques of model checking. The unique aspect of these lectures is the coverage of both theory and practice. The authors have been responsible for one of the most successful experimental systems for probabilistic model checking. These lecture notes are of interest to software engineers, realtime programmers, researchers in machine learning and numerical analysts who may well be interested to see how standard numerical techniques are used in a novel context.
Both sets of lectures are expository and suitable for graduate courses in theoretical computer science and for research mathematicians interested in design and analysis of concurrent and probabilistic computational systems.
Titles in this series are copublished with the Centre de recherches mathématiques.
ReadershipGraduate students and research mathematicians interested in theoretical computer science, specifically the theory of computing models.

Table of Contents

On streams and coinduction

Preface

Acknowledgments

Streams and coinduction

Stream calculus

Analytical differential equations

Coinductive counting

Component connectors

Appendix A. Key differential equations

Bibliography

Modelling and verification of probabilistic systems

Preface

Introduction

Discretetime Markov chains

Markov decision processes

Continuoustime Markov chains

Probabilistic timed automata

Implementation

Appendix A. Measure theory and probability

Appendix B. Iterative solution methods

Bibliography


Additional Material

Reviews

Presents a new way of thinking about concurrency.
CMS Notes


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The book consists of two sets of lecture notes devoted to slightly different methods of analysis of concurrent and probabilistic computational systems.
The first set of lectures develops a calculus of streams (a generalization of the set of natural numbers) based on the coinduction principle coming from the theory of coalgebras. It is now well understood that the interplay between algebra (for describing structure) and coalgebra (for describing dynamics) is crucial for understanding concurrent systems. There is a striking analogy between streams and formula calculus reminiscent of those appearing in quantum calculus. These lecture notes will appeal to anyone working in concurrency theory but also to algebraists and logicians.
The other set of lecture notes focuses on methods for automatically verifying probabilistic systems using techniques of model checking. The unique aspect of these lectures is the coverage of both theory and practice. The authors have been responsible for one of the most successful experimental systems for probabilistic model checking. These lecture notes are of interest to software engineers, realtime programmers, researchers in machine learning and numerical analysts who may well be interested to see how standard numerical techniques are used in a novel context.
Both sets of lectures are expository and suitable for graduate courses in theoretical computer science and for research mathematicians interested in design and analysis of concurrent and probabilistic computational systems.
Titles in this series are copublished with the Centre de recherches mathématiques.
Graduate students and research mathematicians interested in theoretical computer science, specifically the theory of computing models.

On streams and coinduction

Preface

Acknowledgments

Streams and coinduction

Stream calculus

Analytical differential equations

Coinductive counting

Component connectors

Appendix A. Key differential equations

Bibliography

Modelling and verification of probabilistic systems

Preface

Introduction

Discretetime Markov chains

Markov decision processes

Continuoustime Markov chains

Probabilistic timed automata

Implementation

Appendix A. Measure theory and probability

Appendix B. Iterative solution methods

Bibliography

Presents a new way of thinking about concurrency.
CMS Notes