In this third edition of Mark as Story, Rhoads, Dewey, and Michie take their treatment of the Gospel of Mark to new levels. While retaining their clear and thorough analysis of Mark as a narrative, they now place their study of Mark in the context of orality. The new preface explains the role of Mark in a predominantly oral culture. Throughout the study, they refer to the author as composer, the narrator as performer, the Gospel as oral composition, and the audience as gathered communities. The conclusion hypothesizes a performance scenario of Mark in Palestine shortly after the Roman-Judean War of 66 to 70 CE. The new edition also highlights the dimensions of Mark that stand in contrast to imperial worldviews and values. The authors argue that the performance of Mark itself was a means to draw audiences into a non-imperial world based on mutual service rather than hierarchical domination. In so doing, they shift the Gospels center of gravity from the end of the story to the beginning, configuring it not as "a passion narrative with an extended introduction" but as "the arrival of the rule of God with an extended denouement." Performing Mark: The appendices for students at the end of the book that offer exercises to interpret the narrative of Mark now also include "Exercises for Learning and Telling Episodes" from the Gospel of Mark by heart as part of the learning process.

This is the fifteenth volume in the Machine Intelligence series, founded in 1965 by Donald Michie, and includes papers by a number of eminent AI figures including John McCarthy, Alan Robinson, Robert Kowalski and Mike Genesereth. The book is centred on the theme of intelligent agents and covers a wide range of topics, including: - Representations of consciousness (John McCarthy, Stanford University and Donald Michie, Edinburgh University) - SoftBots (Bruce Blumberg, MIT Media Lab) - Parallel implementations of logic (Alan Robinson, Syracuse University) - Machine learning (Stephen Muggleton, Oxford University) - Machine vision (Andrew Blake, Oxford University) - Machine-based scientific discovery in molecular biology (Mike Sternberg, Imperial Cancer Research Fund).