Contents: Introduction; General Markov Chains; Reversible Markov Chains; Hitting and Convergence Time, and Flow Rate, Parameters for Reversible Markov Chains; coupling theory and examples; Special Graphs and Trees; Cover Times; Symmetric Graphs and Chains; Advanced L^2 Techniques for Bounding Mixing Times; A Second Look at General Markov Chains; Some Graph Theory and Randomized Algorithms; Continuous State, Infinite State and Random Environment; Interacting Particles on Finite Graphs; Markov Chain Monte Carlo. |