This book presents the first unified formalization for defining novelty across the span of machine learning, symbolic-reasoning, and control and planning-based systems.  Dealing with novelty, things not previously seen by a system, is a critical issue for building vision-systems and general intelligent systems.  The book presents examples of using this framework to define and evaluate in multiple domains including  image recognition image-based open world learning,  hand-writing and author analysis,  CartPole Control,  Image Captioning, and Monopoly.  Chapters are written by well-known contributors to this new and emerging field.  In addition, examples are provided from multiple areas, such as machine-learning based control problems, symbolic reasoning, and multi-player games. 

Addresses novelty to enhance building both vision-systems and planning-based systems Establishes formal definitions of novelty subtypes that will help produce a consistent lexicon for researchers Includes examples of applications, including image captioning, multi-agent game domain, and handwriting recognition

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