Functions of Predictive Models

What are predictive models good for? Here's what I think:

• Planning - Without an accurate predictive model, it's impossible to generate simulated experiences. Planning requires a predictive model.
  
• Curiosity - The only models of curiosity I've seen so far depend upon prediction. Curiosity is defined as novelty or, even better, the reduction in novelty over time. The only good way to measure novelty in a general way is by comparing the output of a predictive model with reality. This could include a reflexive, metapredictor component that can predict a level of uncertainty about its own predictions.
  
• Attention - I think attention is drawn to unpredicted, novel situations (and novelty measurement depends upon predictive models... see Curiosity above). In other words, the limited attention channel is focused on situations that contain the highest probability of containing useful information. These can be externally driven (unpredicted external stimuli) or internally driven (through planning/simulated experiences, we might come to a novel situation which attracts our attention and may guide external movement toward that situation in the real world).
  

Note that, in any kind of general purpose intelligent agent, predictive models must be learned from experience.