- Suppose we have a connection in a network, where we apply the PES learning rule using an error signal.
Now suppose this error signal comes once every 100 ms defining a 100-timestep epoch of our network (ps from an external simulation) but the network works at a dt of 1 ms. We want the PES to modify the decoders once, not during all 100 timesteps.
How is this possible ? Does it have to do with the pre_tau parameter?
Would it be plausible? Would it be the same just to apply the same error signal for all 100 timesteps just with a lower learning rate?
- It is stated that the PES tries to minimize the error signal provided. That refers to absolute values (therefore 0 error will not change decoders, positive value will change them towards a certain direction and negative towards the opposite?) or the more negative the error the less change will take place (therefore 0 error will change decoders but less than a positive value and more than a negative value?)
In other words error in PES can be considered as both reward and punishment in reinforcement terms?