I thought of two types of neural nets: Reflex and Predictive.
Normal neural nets can produce some seemingly intelligent and complex behaviors but it doesn’t actually involve conscious thought. It can be treated as a reflex, like how when you touch a hot object you pull your hand out without thinking about it or without even realizing it’s hot yet.
Predictive neural nets takes a set of inputs and produces the same set of outputs. Then those outputs are again taken as inputs and will run in a loop. This will be like RNNs but in RNNs, taking outputs as inputs happens at the node level. In predictive neural nets, it happens at the entire network level. The purpose of this is to predict what will happen (output) given a situation (input). Like how when you move forward a little, the object you are looking at will probably look bigger. A mechanism will be created to decide whether to break the loop and start another line of thought. Probably also a mechanism to decide whether the results of the prediction is desirable.
Suppose an AI agent can see, hear and move. Within this agent, both predictive and reflex neural nets act together. A mechanism (another neural net?) will be created to decide whether to follow the reflex, or to take the advice of the predictive neural net.
What do you guys think? Does this exist already? Is it a good idea?
from Artificial Intelligence http://ift.tt/2qGSFYg