; Department of Mathematics; NANDO DE FREITAS; Department of Computer Science, University of British Columbia
; Statistics Group, University of Bristol, University Walk, Bristol BS8 1TW, UK; 2366 Main Mall, Vancouver,; BC V6T 1Z4, Canada
This purpose of this introductory paper is threefold. First, it introduces the Monte Carlo method with emphasis on probabilistic machine learning. Second, it reviews the main building blocks of modern Markov chain Monte Carlo simulation, thereby providing and introduction to the remaining papers of this special issue. Lastly, it discusses new interesting research horizons.