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

The hierarchical organisation of behaviour is a fundamental means through which robots and organisms can acquire and produce a sophisticated and exible behaviour that allows them to solve multiple tasks in multiple conditions. Recently, the research on this topic has been receiving increasing attention. Indeed, machine learning and robotics are recognising its fundamental importance for building robots that scale up to solve more complex tasks, possibly in a cumulative fashion. At the same time, research in psychology and neuroscience is finding a strong evidence that modularity and hierarchy are pivotal organisation principles of behaviour and brain. This book aims to present in a unique venue a review and discussion of some of the most important works produced in the field. To this purpose, the books collects the contributions by authors representing some of the most active and important researchers of the field. Each contribution reviews the main works of the authors, and the open challenges and possible solutions for them. Together the contributions so give a good coverage of the most important models, findings, and challenges of the field. This introduction chapter first presents the general aims and scope of the book and then briefly outlines the contents of the various chapters to allow the readers to orient and focus on those of their interest.