Tag: AIC

Find the Alien

Mark Davis2 Comments

Assembly Theory (AT) (original paper) is some new theoretical chemistry that tries to assess the relative complexity of the molecular underpinnings of life, even when the chemistry might be completely alien. For instance, if we send a probe to a Jovian moon and there are new microscopic creatures in the ocean, how will we figure that out? In AT, it is assumed that all living organisms require a certain complexity in order to function since that is a minimal requirement for life on Earth. The chemists experimentally confirmed that mass spectrometry is a fairly reliable way of differentiating the complexity of living things and their byproducts from other substances. Of course, they only have Earthly living things to test, but they had no false positives in their comparison set of samples, though some substances like beer tended to be unusually high in their spectral analysis. The theory is that when a mass spec ionizes a sample and routes it through a magnetic and electric field, the complexity of the original molecules is represented in the complexity of the spray of molecular masses recorded by the detectors.

But what is “complexity” exactly? There are a great number of candidates, as Seth Lloyd notes in this little round-up paper that I linked to previously. Complexity intuitively involves something like a trade-off between randomness and uniformity, but also reflects internal repetition with variety. There is a mathematical formalism that in full attribution is “Solomonoff-Chaitin-Kolmogorov Complexity”—but we can just call it algorithmic complexity (AC) for short—that has always been an idealized way to think about complexity: take the smallest algorithm (in terms of bits) that can produce a pattern and the length of the algorithm in bits is the complexity.… Read the rest

Bereitschaftspotential and the Rehabilitation of Free Will

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The question of whether we, as people, have free will or not is both abstract and occasionally deeply relevant. We certainly act as if we have something like libertarian free will, and we have built entire systems of justice around this idea, where people are responsible for choices they make that result in harms to others. But that may be somewhat illusory for several reasons. First, if we take a hard deterministic view of the universe as a clockwork-like collection of physical interactions, our wills are just a mindless outcome of a calculation of sorts, driven by a wetware calculator with a state completely determined by molecular history. Second, there has been, until very recently, some experimental evidence that our decision-making occurs before we achieve a conscious realization of the decision itself.

But this latter claim appears to be without merit, as reported in this Atlantic article. Instead, what was previously believed to be signals of brain activity that were related to choice (Bereitschaftspotential) may just be associated with general waves of neural activity. The new experimental evidence puts the timing of action in line with conscious awareness of the decision. More experimental work is needed—as always—but the tentative result suggests a more tightly coupled pairing of conscious awareness with decision making.

Indeed, the results of this newer experimental result gets closer to my suggested model of how modular systems combined with perceptual and environmental uncertainty can combine to produce what is effectively free will (or at least a functional model for a compatibilist position). Jettisoning the Chaitin-Kolmogorov complexity part of that argument and just focusing on the minimal requirements for decision making in the face of uncertainty, we know we need a thresholding apparatus that fires various responses given a multivariate statistical topology.… Read the rest

Free Will and Algorithmic Information Theory (Part II)

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Bad monkey

So we get some mild form of source determinism out of Algorithmic Information Complexity (AIC), but we haven’t addressed the form of free will that deals with moral culpability at all. That free will requires that we, as moral agents, are capable of making choices that have moral consequences. Another way of saying it is that given the same circumstances we could have done otherwise. After all, all we have is a series of if/then statements that must be implemented in wetware and they still respond to known stimuli in deterministic ways. Just responding in model-predictable ways to new stimuli doesn’t amount directly to making choices.

Let’s expand the problem a bit, however. Instead of a lock-and-key recognition of integer “foodstuffs” we have uncertain patterns of foodstuffs and fallible recognition systems. Suddenly we have a probability problem with P(food|n) [or even P(food|q(n)) where q is some perception function] governed by Bayesian statistics. Clearly we expect evolution to optimize towards better models, though we know that all kinds of historical and physical contingencies may derail perfect optimization. Still, if we did have perfect optimization, we know what that would look like for certain types of statistical patterns.

What is an optimal induction machine? AIC and variants have been used to define that machine. First, we have Solomonoff induction from around 1960. But we also have Jorma Rissanen’s Minimum Description Length (MDL) theory from 1978 that casts the problem more in terms of continuous distributions. Variants are available, too, from Minimum Message Length, to Akaike’s Information Criterion (AIC, confusingly again), Bayesian Information Criterion (BIC), and on to Structural Risk Minimization via Vapnik-Chervonenkis learning theory.

All of these theories involve some kind of trade-off between model parameters, the relative complexity of model parameters, and the success of the model on the trained exemplars.… Read the rest