Notes for the Lifebox, the Seashell, and the Soul - Rudy Rucker

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Notes for The Lifebox, the Seashell, and the Soul, by Rudy Rucker quantum mechanics section, but I think it came out alright. Hopelessly dated? I didn’t mention irreversibility. Oh well. I’ve always hated irreversibility. Just write it and mail it in, Ru. Get it done. I need to get back to the main argument of the book. In getting so deep into the physics, I kind of lost the thread. Better reread the eighty (!) pages I’ve written so far and remember where I wanted Chapter One to go. Next up is supposed to be a section on Life, with subsections on Nature, the Mind, and Society. Yesterday I was walking in the woods. Start there? December 11, 2003. Contracts! I finally got the 4W8W contracts from Brockman. He’s really been working it over, says Oakes, “changing the most unexpected things.” But they’re done and they look good. The money’s not so bad. I taught my last class yesterday, so hope to make some progress in getting Chapter One done. Well, finish it by end of January, anyway. Worrying about finding more and fresher computer examples for my section on Life. DNA ~ fractal parameters. Reaction-Diffusion CA ~ Development. Feedback system like flocking boids or balancing unicycle or getting the parameters of a computer game to work ~ metabolism. Wator ~ ecology. Blind watchmaker CA program ~ evolution. In a way there really aren’t so many computer examples. But I feel like there are more than I can put my finger on. January 13 - 14, 2004. What To Say About The Mind? My mind is a stream with ripples I call thoughts (or maybe it’s something else) and (if it’s like a stream) all I can do is throw pebbles into the water. I’ve been pushing for this triad notion that the lifebox and the soul are bridged having the lifebox run an activator-inhibitor rule (like the ones that generates the cone shell patterns or the leopard spots or the bones of your hand). Today I thought some about how to organize this, and in the process I’m having some doubts about the particular applicability of an activator-inhibitor rule (I’ll call it a RD rule for reaction diffusion, I can’t use AI as this would sound like artificial intelligence.) I see a series of levels. Mind level 0: Quantum mind merged with cosmos Merged with the One. The Herbertian quantum mind. The sense of the World. Quantum mind is really only a metaphor, in connection with the brain, but we’ll see that it has a certain validity in the esoteric field of quantum computation. Mind level 1: Neural net reflexes. Neural nets to control reflexes. Like two photosensitive spots connected to a two neurons, each connected to a bending muscle which is also connected to skin muscle. Some simple weights on the sensor inputs. An ability for the neurons to be refractory so they don’t fire all the time. Well understood standard issue neural net type stuff. Think of Genghis the Ant. Note that neural nets aren’t dynamic, not like thoughts. Mind level 2: Ideas as patterns of neural activation. Now comes a somewhat mysterious level at which we form basic ideas. I’m talking p. 124
Notes for The Lifebox, the Seashell, and the Soul, by Rudy Rucker about simple facts like “this ball is red,” or “ head is hairy.” I see ideas as being patterns of neuron firings, like static loops, at least in the shortterm memory. In the long-term memory we probably have something less volatile, like stable geometry of axon dendrites or at least maybe memory biochemicals. But the short term idea is probably electrical. (2a) Patterns of activation and inhibition. To keep something in mind, you keep circling around a little loop or knot or subnetwork, activating perhaps a series of sensory memories blue-hot-hungry-sweet-wet. Maybe inhibition plays a role, in terms of not letting the thought energy branch off into other connections. Think of sand moats with water sloshing around in a circle, the sand is inhibition, the water is activation. This can arise a limit cycle of a process. What controls the motions of activation and inhibition? Could it be an BZ-style rule? One difficulty here is that the activator-inhibitor or reaction-diffusion rules are formulated in terms of CA spaces, and the space of brain neurons doesn’t have that type of structure. It’s a network. But perhaps we could run such a rule over a network. Visualize a 3D CA running a BZ rule and have the cells be nodes connected by strings to their neighbors and stretch a bunch of the strings and scramble things around, maybe drop the mess onto a tabletop and the BZ is still happening, but on casual observation you might not be able to see the scrolls. In the same way, the network of my brain cells can be running an activator inhibitor rule even though no type of brain scan would reveal scrolls. The spatial arrangement of the neurons doesn’t match their connectivity. Actually there probably is some match, so one might expect to see traces of scrolls in the brain activation patterns. [Technical problem: a network doesn’t have the neighborhood structure of a CA, like if A connects to B and A connects to C, that doesn’t imply B is “near” C on a network, thought it does in space. Maybe I could set up an N-d space of some kind to have linked things close? The i-th axis being (1-strength of connection to node i). This is too hard to think about.] Now what is the stuff that spreads the activation and inhibition? Rather than thinking of it as concentrations of chemicals, I could, rather think of it as excitory and inhibitory electrical signals. Suppose each neuron is in a state between -1 and +1 (inhibited vs. excited) and suppose that each has axons leading to other neurons, and that these axons transmit a -1 to +1 signal matching the current activation level of the cell. One thing that makes me pause here is that in Turing stripes and BZ rules, we have the activation and inhibition spreading at different rates. But it seems like an electrical signal be transmitted at the same rate whatever its value. But a neuron could respond at different speeds to different kinds of inputs, might move more slowly into activation and be able to drop abruptly into inhibition, thus effectively giving different rates. In this connection think about things like the Hodge rule or even Brian’s Brain which mimic excitation and inhibition without even having two substances, they get by with simply a range of states. If the process is something like a CA running on a network of neurons, we can ask what is the rule in each neuron. I’ll suggest a complicated and a simple idea. The complicated idea is to have different rules at each neuron. The simple idea is to have the same rule at each neuron. (2b) Complicated neuron rules. I think here of a Stuart Kaufman network. Imagine having N cells, each with k links to randomly chosen other cells, and give each cell a random Boolean function F used as NewVal = F(k inputs), and just put a 0 or 1 in each cell, and p. 125
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Notes for the Lifebox, the Seashell, and the Soul - Rudy Rucker

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