Computing affect in autonomous agents

In previous work we proposed that affect can be modeled in an autonomous agent. We report progress made since then-specifically, an improved understanding of the basis of our approach, a new version of the model used earlier, rationalized both in terms of the underlying neuroscience and the equations used to compute affect. We describe plans for future work to remove constants that we presently have hard coded into the model. We also report some of the difficulties we face: the need for a stronger empirical basis for the equations we use, and the difficulty in identifying success criteria.