The generalized agent

The agent  brain is a polynomial counter, the cells simply count out polynomial patterns. This about all there is to our generalized agent.

We really do count out polynomial patterns. I see this in myself when I run up the stairs, the pattern kicks in, the rhythmic spike train, and my eyes just adjust the Gibbs separation, my eyes a phase lock loop that keeps my feet within Gibbs of the stair edge.

My house is a set of bounded functions, triggered at my walking rate.  The house polynomial done in two independent counters, but synchronized, one for left, right. Gets me around the house, changing directions causes a momentary spiral, but I have left room at the corners of my house for that.

I have a bounded function that defines a quick walk down two blocks, to the family.  Their house is a bounded function, probably bounded by the rate of a walk around.
Most houses and homes are likely bound by the typical waling rate, and rate multiplied up.  We likely have in our mind a quant for say, 12 steps, a distance we unknowningly use, an intermediate count.
Hop, skip and a jump are probably not bad quanta for how we pace. relative to the step. So we can build polynomial spike trains out  of hop and skip.

Seems simple.  All the bounded functions are tied to muscle actions as base rate.  We even have long term bounded functions in which the cells trigger off of biochemical rates, like hunger and long hikes and raising family.  We start the train, but lock it to environmental cues.
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I have a winter bounded function, defines a few things differently.  The Holiday cycles, especially should have a preset pattern.

There is a great advantage, memory goes way up because all memory has this holographic trace, they all synchronize, so we end up with a pattern for virtually any sequence of action, we find something close and entangle!  It is the entanglement that gives this system flexibility, we can take an old pattern and phase lock it to a slightly different environment.  It is modeled as a constant imprecision, allocated to variations in sets of polynomials.

So, the quantization, it is within the bound.  We use polynomials to recognize things and events in real time, vision even. 

Consider a counting the pattern around a car, for example, when we recognize it.  We have literally counted out a walk around the car, and the movement of the hand over it.  These patterns create the bounded function, the brain then collects the phase deviations to compare against smaller polynomials.  That is how we see.   Partition the object using bounded functions, have increasingly small and dens polynomials for detail matching.

Capital Equipment?
Capital equipment is a reliable down counter, we can phase lock to inventory arrivals when they are governed by a more precise Gibbs than anything in our immediate environment. So, even our assumption of constant imprecision holds as we use polynomial space for leisure.