Intelligent Behavior in Animals and Robots

Intelligence takes many forms. This exciting study explores the novel insight, based
on well-established ethological principles, that animals, humans, and autonomous robots can all be
analyzed as multi-task autonomous control systems. Biological adaptive systems, the authors argue,
can in fact provide a better understanding of intelligence and rationality than that provided by
traditional AI.

In this technically sophisticated, clearly written investigation
of robot-animal analogies, McFarland and Bösser show that a bee's accuracy in navigating on a cloudy
day and a moth's simple but effective hearing mechanisms have as much to teach us about intelligent
behavior as human models. In defining intelligent behavior, what matters is the behavioral outcome,
not the nature of the mechanism by which the outcome is achieved. Similarly, in designing robots
capable of intelligent behavior, what matters is the behavioral outcome.

McFarland
and Bösser address the problem of how to assess the consequences of robot behavior in a way that is
meaningful in terms of the robot's intended role, comparing animal and robot in relation to rational
behavior, goal seeking, task accomplishment, learning, and other important theoretical
issues.