Emotional Memory and Adaptive Personalities
Venue
Handbook of Synthetic Emotions and Sociable Robotics, Information Science Reference, an imprint of IGI Global, www.info-sci-ref.com (2009), pp. 391-412
Publication Year
2009
Authors
Anthony Francis, Manish Mehta, Ashwin Ram
BibTeX
Abstract
Believable agents designed for long-term interaction with human users need to adapt
to them in a way which appears emotionally plausible while maintaining a consistent
personality. For short-term interactions in restricted environments, scripting and
state machine techniques can create agents with emotion and personality, but these
methods are labor intensive, hard to extend, and brittle in new environments.
Fortunately, research in memory, emotion and personality in humans and animals
points to a solution to this problem. Emotions focus an animal’s attention on
things it needs to care about, and strong emotions trigger enhanced formation of
memory, enabling the animal to adapt its emotional response to the objects and
situations in its environment. In humans this process becomes reflective: emotional
stress or frustration can trigger re-evaluating past behavior with respect to
personal standards, which in turn can lead to setting new strategies or goals. To
aid the authoring of adaptive agents, we present an artificial intelligence model
inspired by these psychological results in which an emotion model triggers
case-based emotional preference learning and behavioral adaptation guided by
personality models. Our tests of this model on robot pets and embodied characters
show that emotional adaptation can extend the range and increase the behavioral
sophistication of an agent without the need for authoring additional hand-crafted
behaviors.
