From human emotions to robot emotions

The main difficulties that researchers face in understanding emotions are difficulties only because of the narrowmindedness of our views on emotions. We are not able to free ourselves from the notion that emotions are necessarily human emotions. I will argue that if animals have emotions, then so can robots. Studies in neuroscience have shown that animal models, though having limitations, have significantly contributed to our understanding of the functional and mechanistic aspects of emotions. I will suggest that one of the main functions of emotions is to achieve the multi-level communication of simplified but high impact information. The way this function is achieved in the brain depends on the species, and on the specific emotion considered. The classical view that emotions are ‘computed’ by specialized brain centers, such as the ‘limbic system’, is criticized. I will suggest that an ensemble of well-known neurobiological phenomena, together referred to as neuromodulation, provide a useful framework for understanding how emotions arise, are maintained, and interact with other aspects of behavior and cognitive processing. This framework suggests new ways in which robot emotions can be implemented and fulfill their function. There are many inherent aspects of emotions that are extremely difficult to study and to account for. I will start by listing a few of them, and then suggest that it may be more fruitful to focus on the functions of emotions rather than on what emotions are. I will then suggest that animals do in fact have emotions, at least functionally, even though we might not be able to empathize with them. This will lead to the conclusion that, functionally, robots could have emotions as well. I will then briefly 1 New address: Duke University, Biomedical Engineering Department and Center for Cognitive Neuroscience, P.O. Box 90281, Durham, NC 27708-0281. fellous@duke.edu. The author wishes to thank Dr. Michael Arbib for many constructive comments on previous versions of this manuscript. Paper presented at the AAAI Spring 2004 symposium on Architectures for Modeling Emotion: Cross-Disciplinary Foundations. E. Hudlicka and L. Canamero. Copyright © 2004, American Association for Artificial Intelligence (www.aaai.org). All rights reserved. open a new window on the neural bases of emotions that may offer new ways of thinking about implementing robotemotions. Why are emotions so difficult to study? A difficulty in studying human emotions is that here are significant individual differences, based on experiential as well as genetic factors (Rolls, 1998; Ortony, 2002; Davidson, 2003a, b; Ortony et al., 2004). My fear at the sight of a bear may be very different from the fear experienced by a park-ranger who has a better sense for bear-danger and knows how to react. My fear might also be different from that of another individual who has had about the same amount of exposure to bears, but who is more prone to risk-taking behaviors. For emotions such as perceptual fear, the commonalities in expression, experience and underlying neurophysiological mechanisms are large enough between individuals, and between species, so that it can be studied in animal models (LeDoux, 1996). However, the issue of individual differences may be overwhelming for emotions such as love or depression. Naturally occurring human emotions often arise in sequences, or in time varying intensity, and often outlast the stimuli that elicited them. After a Halloween prank, fear may yield to anger at the perpetrators followed by shame at oneself for being angry with neighborhood kids on Halloween. The fear of falling at the start of a roller coaster ride becomes less intense towards the end of the ride, even though the curves and speeds might be very similar. It may therefore be an oversimplification to speak of an emotional ‘state’, because emotions may be intrinsically dynamical phenomena of widely different time constants (from a few seconds for perceptual fear, to hours or days for moods, to months or years for depression or love). This makes the study of emotion more difficult since the emotional (and cognitive) contexts have often to be accounted for. Laboratory studies of emotions try to limit and control these factors. However, one must question the extent to which emotions in such controlled settings resemble the naturally occurring emotions. This problem is even more acute if, as I will suggest below, one of the primary roles of emotion is to