An introduction to neurorobotics that presents approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience.

Neurorobotics is an interdisciplinary field that draws on artificial intelligence, cognitive sciences, computer science, engineering, psychology, neuroscience, and robotics. Because the brain is closely coupled to the body and situated in the environment, neurorobots—autonomous systems modeled after some aspect of the brain—offer a powerful tool for studying neural function and may also be a means for developing autonomous systems with intelligence that rivals that of biological organisms. This textbook introduces approaches and design principles for developing intelligent autonomous systems grounded in biology and neuroscience. It is written for anyone interested in learning about this topic and can be used in cognitive robotics courses for students in psychology, cognitive science, and computer science.

Neurorobotics covers the background and foundations of the field, with information on early neurorobots, relevant principles of neuroscience, learning rules and mechanisms, and reinforcement learning and prediction; neurorobot design principles grounded in neuroscience and principles of neuroscience research; and examples of neurorobots for navigation, developmental robotics, and social robots, presented with the cognitive science and neuroscience background that inspired them. A supplementary website offers videos, robot simulations, and links to software repositories with neurorobot examples.

Tiffany J. Hwu is a research scientist working on projects in autonomous agents and human-machine communication. Jeffrey L. Krichmar is a Professor in the Department of Cognitive Sciences and the Department of Computer Science at the University of California, Irvine, where he teaches courses in artificial intelligence, cognitive robotics, and computational neuroscience.

Preface vii
I Neurorobot Background and Foundations 1
1 Neurorobotics: Origins and Background 3
2 Neuroscience: Background for Creating Neurorobots 17
3 Learning and Memory 49
4 Reinforcement Learning and Prediction 67
II Neurorobot Design Principles 87
5 Neurorobot Design Principles 1: Every Action Has a Reaction 89
6 Neurorobot Design Principles 2: Adaptive Behavior, a Change for the Better 113
7 Neurorobot Design Principles 3: Behavioral Trade-Offs Because Life Is Full of Compromises 135
III Neurorobot Applications 153
8 Neurorobotic Navigation 155
9 Developmental and Social Robotics 183
10 Neurorobotics: Past, Present, and Future 205
Glossary 215
References 221
Index 231