Tag Archives: computation

Final States

Over the last three posts I’ve been exploring the idea of system states and how they might connect with computational theories of mind. I’ve used a full-adder logic circuit as a simple stand-in for the brain — the analog flow and logical gating characteristics of the two are very similar.

In particular I’ve explored the idea that the output state of the system doesn’t reflect its inner working, especially with regard to intermediate states of the system as it generates the desired output (and that output can fluctuate until it “settles” to a valid correct value).

Here I plan to wrap up and summarize the system states exploration.

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Intermediate States

I left off last time talking about intermediate, or transitory, states of a system. The question is, if we only look at the system at certain key points that we think matter, do any intermediate states make a difference?

In a standard digital computer, the answer is a definite no. Even in many kinds of analog computers, transitory states exist for the same reason they do in digital computers (signals flowing through different paths and arriving at the key points at different times). In both cases they are ignored. Only the stable final state matters.

So in the brain, what are the key points? What states matter?

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State of the System

State DiagramIn the last post I talked about software models for a full-adder logic circuit. I broke them into two broad categories: models of an abstraction, and models of a physical instance. Because the post was long, I was able to mention the code implementations only in passing (but there are links).

I want to talk a little more about those two categories, especially the latter, and in particular an implementation that bridges between the categories. It’s here that ideas about simulating the brain or mind become important. Most approaches involve some kind of simulation.

One type of simulation involves the states of a system.

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Full-Adder “Computing”

Full Adder Logic TableImagine the watershed for a river. Every drop of water that falls in that area, if it doesn’t evaporate or sink into the ground, eventually makes its way, through creeks, streams, and rivers, to the lake or ocean that is the shed’s final destination. The visual image is somewhat like the veins in a leaf. Or the branches of the leaf’s tree.

In all cases, there is a natural flow through channels sculpted over time by physical forces. Water always flows downhill, and it erodes what it flows past, so gravity, time, and the resistance of rock and dirt, sculpt the watershed.

The question is whether the water “computes.”

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Interpreting AND as OR

Previously, I wrote that I’m skeptical of interpretation as an analytic tool. In physical reality, generally speaking, I think there is a single correct interpretation (more of a true account than an interpretation). Every other interpretation is a fiction, usually made obvious by complexity and entropy.

I recently encountered an argument for interpretation that involved the truth table for the boolean logical AND being seen — if one inverts the interpretation of all the values — as the truth table for the logical OR.

It turns out to be a tautology. A logical AND mirrors a logical OR.

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Math Games #1

Back at the start of March Mathness I promised the math would be “fun” (really!), but anyone would be forgiven for thinking the previous two posts about Special Relativity weren’t all that much “fun.” (I really enjoy stuff like that, so it’s fun for me, but there’s no question it’s not everyone’s cup of tea.)

Trying to reach for something a bit lighter and potentially more appealing as the promised “fun,” I present, for your dining and dancing pleasure, a trio of number games that anyone can play and which might just tug at the corners of your enjoyment.

We can start with 277777788888899 (and why it’s special).

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