by Prakash Panangaden (McGill University, Canada)

Table of Contents (85k)
Preface (51k)
Chapter 1: Introduction (177k)

Labelled Markov processes are probabilistic versions of labelled transition systems with continuous state spaces. The book covers basic probability and measure theory on continuous state spaces and then develops the theory of LMPs.

The main topics covered are bisimulation, the logical characterization of bisimulation, metrics and approximation theory. An unusual feature of the book is the connection made with categorical and domain theoretic concepts.

• Introduction
• Measure Theory
• Integration
• The Radon-Nikodym Theorem
• A Category of Stochastic Relations
• Probability Theory on Continuous Spaces
• Bisimulation for Labelled Markov Processes
• Metrics for Labelled Markov Processes
• Approximating Labelled Markov Processes
• Approximating the Approximation
• A Domain of Labelled Markov Processes
• Real-Time and Continuous Stochastic Logic
• Related Work