Computational and robotic models of the hierarchical organization of behavior: An overview

Abstract

The hierarchical organisation of behaviour is a fundamental means through which robots and organisms can acquire and produce sophisticated and flexible behaviours that allow them to solve multiple tasks in multiple conditions. Recently, the research on this topic has been receiving increasing attention. On the one hand, machine learning and robotics are recognising the fundamental importance of the hierarchical organisation of behaviour for building robots that scale up to solve complex tasks, possibly in a cumulative fashion. On the other hand, research in psychology and neuroscience is finding increasing evidence that modularity and hierarchy are pivotal organisation principles of behaviour and of the brain. This book reviews the state of the art in computational and robotic models of the hierarchical organisation of behaviour. Each contribution reviews the main works of the authors on this subject, the open challenges, and promising research directions. Together, the contributions give a good coverage of the most important models, findings, and challenges of the field. This introductory chapter presents the general aims and scope of the book and briefly summarises the contents of each chapter.