From Emotions to Artificial Intelligence
To most AI developers, such research in biologically plausible emotion systems sounds extremely promising. In many cases, however, the main goal is to improve upon classical AI instead. Traditional approaches with strong representation and rigorous search mechanisms can benefit tremendously from instinctive reactions and subjective preferences; in fact, that's the premise of this book (learning and reactive behaviors). In many ways, artificial emotions—and the reactive AI techniques used to produce them—represent an ideal complement to classical AI.
On the other hand, the whole concept of artificial emotions is easily blown out of proportion (just as reactive AI is not a silver bullet). Emotions also have their pitfalls; they are not easily controlled, very inflexible, and are hard to understand.
Emotions are a small part of evolution's approach to creating intelligent species. Engineering generally produces very different solutions than evolution; it's very likely engineers will create intelligence with little or no resemblance to biological emotions—although some concepts may be similar (for instance, reactive actions or heuristics). So although emotions are not what make us intelligent, they define us as humans. Therein reside our interests from a game developer's perspective: emotions are a key factor in realism and believability.