Endowing Artificial Systems with Anticipatory Capabilities: Success Cases

Abstract

This book has provided various theoretical perspectives on anticipatory processes in natural and artificial cognitive systems. Advantages have been proposed and confirmed in various detailed case studies, which may have given the reader detailed insights into anticipatory processes and their importance in various cognitive systems tasks. To wrap up these advantages and give a concluding overview of various current anticipatory process advantages, this final chapter highlights a concise collection of precise success stories of anticipations in artificial cognitive systems.

We survey fourteen case studies, which were developed during the EU project MindRACES. In these studies, simulated or real robots were tested in different environmental tasks, which required advanced sensorimotor and cognitive abilities. These abilities included the initiation and control of goal-directed actions, the orientation of attention, finding and reaching goal locations, and performing mental experiments for action selection. All the studies have shown advantages of anticipatory mechanisms compared to reactive mechanisms in terms of increased robot autonomy and adaptivity. In some cases, anticipations even caused the development of new cognitive abilities, which were simply impossible without anticipatory mechanisms. For each case study, we indicate relevant associated publications, in which the interested reader may find further details on the relevant computational architectures, the involved anticipatory mechanisms, as well as on the analytical and quantitative results.

While the book as a whole has laid out the theoretical principles and design methodology for such advancements, this final chapter thus provides various possible starting points for further developments in both the surveyed system architectures and the presented solutions to the cognitive tasks addressed.

MindRACES: From Reactive to Anticipatory Cognitive Embodied Systems; funded under grant FP6-511931 under the “Cognitive Systems” initiative from the EC.